From 919752840ed2f7f69475b2187790865de16eee6b Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Wed, 25 Sep 2019 15:58:07 +0200
Subject: [PATCH 01/21] Add new configuration for runtime benchmarks

---
 bench-run/src/main/scala/Benchmarks.scala | 110 ++++++++++++++++++++++
 build.sbt                                 |   1 +
 project/Build.scala                       |   1 +
 3 files changed, 112 insertions(+)
 create mode 100644 bench-run/src/main/scala/Benchmarks.scala

diff --git a/bench-run/src/main/scala/Benchmarks.scala b/bench-run/src/main/scala/Benchmarks.scala
new file mode 100644
index 000000000000..d70a2ae80469
--- /dev/null
+++ b/bench-run/src/main/scala/Benchmarks.scala
@@ -0,0 +1,110 @@
+package dotty.tools.benchmarks
+
+import dotty.tools.dotc._
+import core.Contexts.Context
+import dotty.tools.FatalError
+import reporting._
+
+import org.openjdk.jmh.results.RunResult
+import org.openjdk.jmh.runner.Runner
+import org.openjdk.jmh.runner.options.OptionsBuilder
+import org.openjdk.jmh.annotations._
+import org.openjdk.jmh.results.format._
+import java.util.concurrent.TimeUnit
+
+import scala.runtime.DynamicTuple
+
+object Bench {
+  def main(args: Array[String]): Unit = {
+    val (intArgs, args1) = args.span(x => try { x.toInt; true } catch { case _: Throwable => false } )
+
+    val warmup = if (intArgs.length > 0) intArgs(0).toInt else 30
+    val iterations = if (intArgs.length > 1) intArgs(1).toInt else 20
+    val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
+
+    val opts = new OptionsBuilder()
+               .shouldFailOnError(true)
+               .jvmArgs("-Xms2G", "-Xmx2G")
+               .mode(Mode.AverageTime)
+               .timeUnit(TimeUnit.NANOSECONDS)
+               .warmupIterations(warmup)
+               .measurementIterations(iterations)
+               .forks(forks)
+               .build
+
+    val runner = new Runner(opts) // full access to all JMH features, you can also provide a custom output Format here
+    runner.run() // actually run the benchmarks
+  }
+}
+
+@State(Scope.Thread)
+class ConsConcatBenchmarks {
+  @Param(Array("10", "20"))
+  var size: Int = _
+  var tuple: Tuple = _
+
+  @Setup
+  def setup(): Unit = {
+    tuple = ()
+
+    for (i <- 1 to size)
+      tuple = "string" *: tuple
+  }
+
+  @Benchmark
+  def baseline(): Unit = {}
+
+  // Cons benchmarks
+  @Benchmark
+  def tupleCons(): Tuple = {
+    "string" *: tuple
+  }
+
+  @Benchmark
+  def dynamicTupleCons(): Tuple = {
+    DynamicTuple.dynamicCons("string", tuple)
+  }
+
+  // Concat benchmarks
+  @Benchmark
+  def tupleConcat(): Tuple = {
+   tuple ++ tuple
+  }
+
+  @Benchmark
+  def dynamicTupleConcat(): Tuple = {
+    DynamicTuple.dynamicConcat(tuple, tuple)
+  }
+
+  // Interesting behaviour : I expect the two following to be the same because of TupleOptimizations.scala
+  @Benchmark
+  def tupleConcat2(): Tuple = {
+    ("string", "string") ++ ("string", "string")
+  }
+
+  @Benchmark
+  def tupleNoConcat(): Tuple = {
+    ("string", "string", "string", "string")
+  }
+}
+
+@State(Scope.Thread)
+class ApplyBenchmarks {
+  val size: Int = 100
+
+  val tuple: NonEmptyTuple = {
+    var t = ()
+    for (i <- 1 to size)
+      t = "string" *: t
+    t.asInstanceOf[NonEmptyTuple]
+  }
+
+  @Param(Array("1", "10", "25", "50", "75", "99"))
+  var index: Int = _
+
+  // Apply benchmarks, doesn't work for some reason
+  // @Benchmark
+  // def tupleApply(): Unit = {
+  //   DynamicTuple.dynamicApply(tuple, index)
+  // }
+}
diff --git a/build.sbt b/build.sbt
index ce2d153fae34..54f8fe6bd63a 100644
--- a/build.sbt
+++ b/build.sbt
@@ -19,6 +19,7 @@ val `tasty-core-bootstrapped` = Build.`tasty-core-bootstrapped`
 val `tasty-core-scala2` = Build.`tasty-core-scala2`
 val `dotty-tastydoc` = Build.`dotty-tastydoc`
 val `dotty-tastydoc-input` = Build.`dotty-tastydoc-input`
+val `dotty-bench-run` = Build.`dotty-bench-run`
 val `scala-library` = Build.`scala-library`
 val `scala-compiler` = Build.`scala-compiler`
 val `scala-reflect` = Build.`scala-reflect`
diff --git a/project/Build.scala b/project/Build.scala
index 8bfe90f11955..3f3f1f958450 100644
--- a/project/Build.scala
+++ b/project/Build.scala
@@ -1042,6 +1042,7 @@ object Build {
 
   lazy val `dotty-bench` = project.in(file("bench")).asDottyBench(NonBootstrapped)
   lazy val `dotty-bench-bootstrapped` = project.in(file("bench")).asDottyBench(Bootstrapped)
+  lazy val `dotty-bench-run` = project.in(file("bench-run")).asDottyBench(Bootstrapped)
 
   lazy val `dotty-tastydoc` = project.in(file("tastydoc")).asDottyTastydoc(Bootstrapped)
   lazy val `dotty-tastydoc-input` = project.in(file("tastydoc/input")).asDottyTastydocInput(Bootstrapped)

From 013b93cfd9d25e41b7077d7b56b1d385c4611d70 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Sun, 29 Sep 2019 12:49:20 +0200
Subject: [PATCH 02/21] Add output file support and benchmark filtering

---
 bench-run/src/main/scala/Benchmarks.scala    | 78 ++-----------------
 bench-run/src/main/scala/tuples/Tuples.scala | 79 ++++++++++++++++++++
 2 files changed, 85 insertions(+), 72 deletions(-)
 create mode 100644 bench-run/src/main/scala/tuples/Tuples.scala

diff --git a/bench-run/src/main/scala/Benchmarks.scala b/bench-run/src/main/scala/Benchmarks.scala
index d70a2ae80469..a8e47646eb63 100644
--- a/bench-run/src/main/scala/Benchmarks.scala
+++ b/bench-run/src/main/scala/Benchmarks.scala
@@ -22,6 +22,9 @@ object Bench {
     val iterations = if (intArgs.length > 1) intArgs(1).toInt else 20
     val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
 
+    val benchmarks = if (args1.length > 0) args1(0) else ".*"
+    val outputFile = if (args1.length > 1) args1(1) else "output.csv"
+
     val opts = new OptionsBuilder()
                .shouldFailOnError(true)
                .jvmArgs("-Xms2G", "-Xmx2G")
@@ -30,81 +33,12 @@ object Bench {
                .warmupIterations(warmup)
                .measurementIterations(iterations)
                .forks(forks)
+               .include(benchmarks)
+               .resultFormat(ResultFormatType.CSV)
+               .result("results/" ++ outputFile)
                .build
 
     val runner = new Runner(opts) // full access to all JMH features, you can also provide a custom output Format here
     runner.run() // actually run the benchmarks
   }
 }
-
-@State(Scope.Thread)
-class ConsConcatBenchmarks {
-  @Param(Array("10", "20"))
-  var size: Int = _
-  var tuple: Tuple = _
-
-  @Setup
-  def setup(): Unit = {
-    tuple = ()
-
-    for (i <- 1 to size)
-      tuple = "string" *: tuple
-  }
-
-  @Benchmark
-  def baseline(): Unit = {}
-
-  // Cons benchmarks
-  @Benchmark
-  def tupleCons(): Tuple = {
-    "string" *: tuple
-  }
-
-  @Benchmark
-  def dynamicTupleCons(): Tuple = {
-    DynamicTuple.dynamicCons("string", tuple)
-  }
-
-  // Concat benchmarks
-  @Benchmark
-  def tupleConcat(): Tuple = {
-   tuple ++ tuple
-  }
-
-  @Benchmark
-  def dynamicTupleConcat(): Tuple = {
-    DynamicTuple.dynamicConcat(tuple, tuple)
-  }
-
-  // Interesting behaviour : I expect the two following to be the same because of TupleOptimizations.scala
-  @Benchmark
-  def tupleConcat2(): Tuple = {
-    ("string", "string") ++ ("string", "string")
-  }
-
-  @Benchmark
-  def tupleNoConcat(): Tuple = {
-    ("string", "string", "string", "string")
-  }
-}
-
-@State(Scope.Thread)
-class ApplyBenchmarks {
-  val size: Int = 100
-
-  val tuple: NonEmptyTuple = {
-    var t = ()
-    for (i <- 1 to size)
-      t = "string" *: t
-    t.asInstanceOf[NonEmptyTuple]
-  }
-
-  @Param(Array("1", "10", "25", "50", "75", "99"))
-  var index: Int = _
-
-  // Apply benchmarks, doesn't work for some reason
-  // @Benchmark
-  // def tupleApply(): Unit = {
-  //   DynamicTuple.dynamicApply(tuple, index)
-  // }
-}
diff --git a/bench-run/src/main/scala/tuples/Tuples.scala b/bench-run/src/main/scala/tuples/Tuples.scala
new file mode 100644
index 000000000000..ba2d14e76041
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/Tuples.scala
@@ -0,0 +1,79 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+import scala.runtime.DynamicTuple
+
+@State(Scope.Thread)
+class ConsConcatBenchmarks {
+  @Param(Array("10", "20"))
+  var size: Int = _
+  var tuple: Tuple = _
+
+  @Setup
+  def setup(): Unit = {
+    tuple = ()
+
+    for (i <- 1 to size)
+      tuple = "string" *: tuple
+  }
+
+  @Benchmark
+  def baseline(): Unit = {}
+
+  // Cons benchmarks
+  @Benchmark
+  def tupleCons(): Tuple = {
+    "string" *: tuple
+  }
+
+  @Benchmark
+  def dynamicTupleCons(): Tuple = {
+    DynamicTuple.dynamicCons("string", tuple)
+  }
+
+  // Concat benchmarks
+  @Benchmark
+  def tupleConcat(): Tuple = {
+   tuple ++ tuple
+  }
+
+  @Benchmark
+  def dynamicTupleConcat(): Tuple = {
+    DynamicTuple.dynamicConcat(tuple, tuple)
+  }
+
+  // Interesting behaviour : I expect the two following to be the same because of TupleOptimizations.scala
+  @Benchmark
+  def tupleConcat2(): Tuple = {
+    ("string", "string") ++ ("string", "string")
+  }
+
+  @Benchmark
+  def tupleNoConcat(): Tuple = {
+    ("string", "string", "string", "string")
+  }
+}
+
+@State(Scope.Thread)
+class ApplyBenchmarks {
+  val size: Int = 100
+
+  val tuple: NonEmptyTuple = {
+    var t: Tuple = ()
+    for (i <- 1 to size)
+      t = "string" *: t
+    t.asInstanceOf[NonEmptyTuple]
+  }
+
+  @Param(Array("1", "10", "25", "50", "75", "99"))
+  var index: Int = _
+
+  @Benchmark
+  def baseline(): Unit = {}
+
+  // Apply benchmarks, doesn't work for some reason
+  // @Benchmark
+  // def tupleApply(): Unit = {
+  //   DynamicTuple.dynamicApply(tuple, index)
+  // }
+}

From 62a0c280193b92ae16dd7c6f2631539a860858b7 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Sun, 29 Sep 2019 16:01:12 +0200
Subject: [PATCH 03/21] Add input facilities to benchmarks and start making
 serious benchmarks

---
 bench-run/inputs/concat.txt                   |  1 +
 bench-run/outputs/concat.csv                  |  0
 .../scala/{Benchmarks.scala => Main.scala}    | 30 ++++---
 bench-run/src/main/scala/tuples/Apply.scala   | 35 ++++++++
 bench-run/src/main/scala/tuples/Concat.scala  | 64 +++++++++++++++
 bench-run/src/main/scala/tuples/Tuples.scala  | 79 -------------------
 bench/src/main/scala/Benchmarks.scala         |  1 -
 7 files changed, 118 insertions(+), 92 deletions(-)
 create mode 100644 bench-run/inputs/concat.txt
 create mode 100644 bench-run/outputs/concat.csv
 rename bench-run/src/main/scala/{Benchmarks.scala => Main.scala} (61%)
 create mode 100644 bench-run/src/main/scala/tuples/Apply.scala
 create mode 100644 bench-run/src/main/scala/tuples/Concat.scala
 delete mode 100644 bench-run/src/main/scala/tuples/Tuples.scala

diff --git a/bench-run/inputs/concat.txt b/bench-run/inputs/concat.txt
new file mode 100644
index 000000000000..7368b1fc8685
--- /dev/null
+++ b/bench-run/inputs/concat.txt
@@ -0,0 +1 @@
+sizes:0 0,0 5,0 10,0 15,0 20,0 25,0 30,5 0,5 5,5 10,5 15,5 20,5 25,5 30,10 0,10 5,10 10,10 15,10 20,10 25,10 30,15 0,15 5,15 10,15 15,15 20,15 25,15 30,20 0,20 5,20 10,20 15,20 20,20 25,20 30,25 0,25 5,25 10,25 15,25 20,25 25,25 30,30 0,30 5,30 10,30 15,30 20,30 25,30 30
\ No newline at end of file
diff --git a/bench-run/outputs/concat.csv b/bench-run/outputs/concat.csv
new file mode 100644
index 000000000000..e69de29bb2d1
diff --git a/bench-run/src/main/scala/Benchmarks.scala b/bench-run/src/main/scala/Main.scala
similarity index 61%
rename from bench-run/src/main/scala/Benchmarks.scala
rename to bench-run/src/main/scala/Main.scala
index a8e47646eb63..6a937d4faf2b 100644
--- a/bench-run/src/main/scala/Benchmarks.scala
+++ b/bench-run/src/main/scala/Main.scala
@@ -1,10 +1,5 @@
 package dotty.tools.benchmarks
 
-import dotty.tools.dotc._
-import core.Contexts.Context
-import dotty.tools.FatalError
-import reporting._
-
 import org.openjdk.jmh.results.RunResult
 import org.openjdk.jmh.runner.Runner
 import org.openjdk.jmh.runner.options.OptionsBuilder
@@ -12,7 +7,7 @@ import org.openjdk.jmh.annotations._
 import org.openjdk.jmh.results.format._
 import java.util.concurrent.TimeUnit
 
-import scala.runtime.DynamicTuple
+import scala.io.Source
 
 object Bench {
   def main(args: Array[String]): Unit = {
@@ -23,9 +18,9 @@ object Bench {
     val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
 
     val benchmarks = if (args1.length > 0) args1(0) else ".*"
-    val outputFile = if (args1.length > 1) args1(1) else "output.csv"
+    val outputFile = if (args1.length > 2) args1(2) else "output.csv"
 
-    val opts = new OptionsBuilder()
+    var builder = new OptionsBuilder()
                .shouldFailOnError(true)
                .jvmArgs("-Xms2G", "-Xmx2G")
                .mode(Mode.AverageTime)
@@ -35,10 +30,21 @@ object Bench {
                .forks(forks)
                .include(benchmarks)
                .resultFormat(ResultFormatType.CSV)
-               .result("results/" ++ outputFile)
-               .build
+               .result(outputFile)
+
+    if (args1.length > 1) {
+      for ((param, values) <- paramsFromFile(args1(1)))
+        builder = builder.param(param, values: _*)
+    }
+
+    val runner = new Runner(builder.build) // full access to all JMH features, you can also provide a custom output Format here
+    runner.run // actually run the benchmarks
+  }
 
-    val runner = new Runner(opts) // full access to all JMH features, you can also provide a custom output Format here
-    runner.run() // actually run the benchmarks
+  def paramsFromFile(file: String): Array[(String, Array[String])] = {
+    Source.fromFile(file).getLines.toArray.map { l =>
+      val Array(param, values) = l split ':'
+      (param, values split ',')
+    }
   }
 }
diff --git a/bench-run/src/main/scala/tuples/Apply.scala b/bench-run/src/main/scala/tuples/Apply.scala
new file mode 100644
index 000000000000..cdb9e261053e
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/Apply.scala
@@ -0,0 +1,35 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+import scala.runtime.DynamicTuple
+
+@State(Scope.Thread)
+class ApplyBenchmarks {
+  @Param(Array("1 0"))
+  var sizeAndIndex: String = _
+  var tuple: NonEmptyTuple = _
+  var index: Int = _
+
+  @Setup
+  def setup(): Unit = {
+    val size = sizeAndIndex.split(' ')(0).toInt
+    index = sizeAndIndex.split(' ')(1).toInt
+    tuple = "elem" *: ()
+
+    for (i <- 1 until size)
+      tuple = "string" *: tuple
+  }
+
+  @Benchmark
+  def baseline(): Unit = {}
+
+  @Benchmark
+  def normal(): Any = {
+    tuple(index)
+  }
+
+  @Benchmark
+  def inlined(): Any = {
+    DynamicTuple.dynamicApply(tuple, index)
+  }
+}
diff --git a/bench-run/src/main/scala/tuples/Concat.scala b/bench-run/src/main/scala/tuples/Concat.scala
new file mode 100644
index 000000000000..978c6abeff1a
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/Concat.scala
@@ -0,0 +1,64 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+import org.openjdk.jmh.infra.Blackhole
+import scala.runtime.DynamicTuple
+
+@State(Scope.Thread)
+class Concat {
+  @Param(Array("0 0"))
+  var sizes: String = _
+  var tuple1: Tuple = _
+  var tuple2: Tuple = _
+  var array1: Array[Object] = _
+  var array2: Array[Object] = _
+
+  def tupleOfSize(n: Int): Tuple = {
+    var t: Tuple = ()
+    for (i <- 1 to n)
+      t = "elem" *: t
+    t
+  }
+
+  @Setup
+  def setup(): Unit = {
+    val size1 = sizes.split(' ')(0).toInt
+    val size2 = sizes.split(' ')(1).toInt
+    tuple1 = tupleOfSize(size1)
+    tuple1 = tupleOfSize(size2)
+    array1 = Array.fill(size1)("elem")
+    array2 = Array.fill(size2)("elem")
+  }
+
+  @Benchmark
+  def baseline(): Unit = {}
+
+  @Benchmark
+  def normal(): Tuple = {
+   tuple1 ++ tuple2
+  }
+
+  @Benchmark
+  def inlined(): Tuple = {
+    DynamicTuple.dynamicConcat(tuple1, tuple2)
+  }
+
+  // This part is here to try and measure the overhead of tranforming tuples to arrays, then concatenating
+  // the array, and then transforming back to a tuple
+  @Benchmark
+  def toArray(bh: Blackhole): Unit = {
+    bh.consume(DynamicTuple.dynamicToArray(tuple1))
+    bh.consume(DynamicTuple.dynamicToArray(tuple2))
+  }
+
+  @Benchmark
+  def arrayConcat(): Array[Object] = {
+    array1 ++ array2
+  }
+
+  @Benchmark
+  def fromArray(bh: Blackhole): Unit = {
+    bh.consume(DynamicTuple.dynamicFromArray[Tuple](array1))
+    bh.consume(DynamicTuple.dynamicFromArray[Tuple](array2))
+  }
+}
diff --git a/bench-run/src/main/scala/tuples/Tuples.scala b/bench-run/src/main/scala/tuples/Tuples.scala
deleted file mode 100644
index ba2d14e76041..000000000000
--- a/bench-run/src/main/scala/tuples/Tuples.scala
+++ /dev/null
@@ -1,79 +0,0 @@
-package dotty.tools.benchmarks.tuples
-
-import org.openjdk.jmh.annotations._
-import scala.runtime.DynamicTuple
-
-@State(Scope.Thread)
-class ConsConcatBenchmarks {
-  @Param(Array("10", "20"))
-  var size: Int = _
-  var tuple: Tuple = _
-
-  @Setup
-  def setup(): Unit = {
-    tuple = ()
-
-    for (i <- 1 to size)
-      tuple = "string" *: tuple
-  }
-
-  @Benchmark
-  def baseline(): Unit = {}
-
-  // Cons benchmarks
-  @Benchmark
-  def tupleCons(): Tuple = {
-    "string" *: tuple
-  }
-
-  @Benchmark
-  def dynamicTupleCons(): Tuple = {
-    DynamicTuple.dynamicCons("string", tuple)
-  }
-
-  // Concat benchmarks
-  @Benchmark
-  def tupleConcat(): Tuple = {
-   tuple ++ tuple
-  }
-
-  @Benchmark
-  def dynamicTupleConcat(): Tuple = {
-    DynamicTuple.dynamicConcat(tuple, tuple)
-  }
-
-  // Interesting behaviour : I expect the two following to be the same because of TupleOptimizations.scala
-  @Benchmark
-  def tupleConcat2(): Tuple = {
-    ("string", "string") ++ ("string", "string")
-  }
-
-  @Benchmark
-  def tupleNoConcat(): Tuple = {
-    ("string", "string", "string", "string")
-  }
-}
-
-@State(Scope.Thread)
-class ApplyBenchmarks {
-  val size: Int = 100
-
-  val tuple: NonEmptyTuple = {
-    var t: Tuple = ()
-    for (i <- 1 to size)
-      t = "string" *: t
-    t.asInstanceOf[NonEmptyTuple]
-  }
-
-  @Param(Array("1", "10", "25", "50", "75", "99"))
-  var index: Int = _
-
-  @Benchmark
-  def baseline(): Unit = {}
-
-  // Apply benchmarks, doesn't work for some reason
-  // @Benchmark
-  // def tupleApply(): Unit = {
-  //   DynamicTuple.dynamicApply(tuple, index)
-  // }
-}
diff --git a/bench/src/main/scala/Benchmarks.scala b/bench/src/main/scala/Benchmarks.scala
index 779579cd1c6b..86b967762fb6 100644
--- a/bench/src/main/scala/Benchmarks.scala
+++ b/bench/src/main/scala/Benchmarks.scala
@@ -30,7 +30,6 @@ object Bench {
     val iterations = if (intArgs.length > 1) intArgs(1).toInt else 20
     val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
 
-
     import File.{ separator => sep }
 
     val args2 = args1.map { arg =>

From 0cdf81ee558dffd910c368f55eedbed4f5db463b Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Tue, 1 Oct 2019 22:09:34 +0200
Subject: [PATCH 04/21] Create detailed benchmarks about tuples

---
 bench-run/outputs/concat.csv                  |  0
 bench-run/src/main/scala/tuples/Apply.scala   |  4 +-
 .../src/main/scala/tuples/ArrayOps.scala      | 47 +++++++++++++++++++
 bench-run/src/main/scala/tuples/Concat.scala  |  2 +-
 bench-run/src/main/scala/tuples/Cons.scala    | 41 ++++++++++++++++
 5 files changed, 91 insertions(+), 3 deletions(-)
 delete mode 100644 bench-run/outputs/concat.csv
 create mode 100644 bench-run/src/main/scala/tuples/ArrayOps.scala
 create mode 100644 bench-run/src/main/scala/tuples/Cons.scala

diff --git a/bench-run/outputs/concat.csv b/bench-run/outputs/concat.csv
deleted file mode 100644
index e69de29bb2d1..000000000000
diff --git a/bench-run/src/main/scala/tuples/Apply.scala b/bench-run/src/main/scala/tuples/Apply.scala
index cdb9e261053e..7df788cb2efc 100644
--- a/bench-run/src/main/scala/tuples/Apply.scala
+++ b/bench-run/src/main/scala/tuples/Apply.scala
@@ -4,7 +4,7 @@ import org.openjdk.jmh.annotations._
 import scala.runtime.DynamicTuple
 
 @State(Scope.Thread)
-class ApplyBenchmarks {
+class Apply {
   @Param(Array("1 0"))
   var sizeAndIndex: String = _
   var tuple: NonEmptyTuple = _
@@ -17,7 +17,7 @@ class ApplyBenchmarks {
     tuple = "elem" *: ()
 
     for (i <- 1 until size)
-      tuple = "string" *: tuple
+      tuple = "elem" *: tuple
   }
 
   @Benchmark
diff --git a/bench-run/src/main/scala/tuples/ArrayOps.scala b/bench-run/src/main/scala/tuples/ArrayOps.scala
new file mode 100644
index 000000000000..e14e1c996167
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/ArrayOps.scala
@@ -0,0 +1,47 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+import scala.runtime.DynamicTuple
+
+@State(Scope.Thread)
+class ArrayOps {
+  @Param(Array("0"))
+  var size: Int = _
+  var tuple: Tuple = _
+  var array: Array[Object] = _
+  var iarray: IArray[Object] = _
+
+  @Setup
+  def setup(): Unit = {
+    tuple = ()
+
+    for (i <- 1 to size)
+      tuple = "elem" *: tuple
+
+    array = Array.fill(size)("elem")
+    iarray = IArray.fill(size)("elem")
+  }
+
+  @Benchmark
+  def baseline(): Unit = {}
+
+  @Benchmark
+  def toArray(): Array[Object] = {
+    DynamicTuple.dynamicToArray(tuple)
+  }
+
+  @Benchmark
+  def toIArray(): IArray[Object] = {
+    DynamicTuple.dynamicToIArray(tuple)
+  }
+
+  @Benchmark
+  def fromArray(): Tuple = {
+    DynamicTuple.dynamicFromArray(array)
+  }
+
+  @Benchmark
+  def fromIArray(): Tuple = {
+    DynamicTuple.dynamicFromIArray(iarray)
+  }
+}
diff --git a/bench-run/src/main/scala/tuples/Concat.scala b/bench-run/src/main/scala/tuples/Concat.scala
index 978c6abeff1a..63b023322d4b 100644
--- a/bench-run/src/main/scala/tuples/Concat.scala
+++ b/bench-run/src/main/scala/tuples/Concat.scala
@@ -25,7 +25,7 @@ class Concat {
     val size1 = sizes.split(' ')(0).toInt
     val size2 = sizes.split(' ')(1).toInt
     tuple1 = tupleOfSize(size1)
-    tuple1 = tupleOfSize(size2)
+    tuple2 = tupleOfSize(size2)
     array1 = Array.fill(size1)("elem")
     array2 = Array.fill(size2)("elem")
   }
diff --git a/bench-run/src/main/scala/tuples/Cons.scala b/bench-run/src/main/scala/tuples/Cons.scala
new file mode 100644
index 000000000000..c5c68efcca1c
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/Cons.scala
@@ -0,0 +1,41 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+import scala.runtime.DynamicTuple
+
+@State(Scope.Thread)
+class Cons {
+  @Param(Array("0"))
+  var size: Int = _
+  var tuple: Tuple = _
+  var array: Array[Object] = _
+
+  @Setup
+  def setup(): Unit = {
+    tuple = ()
+
+    for (i <- 1 to size)
+      tuple = "elem" *: tuple
+
+    array = Array.fill(size)("elem")
+  }
+
+  @Benchmark
+  def baseline(): Unit = {}
+
+  @Benchmark
+  def normal(): Tuple = {
+    "elem" *: tuple
+  }
+
+  @Benchmark
+  def inlined(): Tuple = {
+    DynamicTuple.dynamicCons("elem", tuple)
+  }
+
+  // This part is here to measure the performance of dong a cons on arrays directly
+  @Benchmark
+  def arrayCons(): Array[Object] = {
+    DynamicTuple.cons$Array("elem", array)
+  }
+}

From 049a3adce53c83c629a3cea963fe57f07d14a57f Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Tue, 1 Oct 2019 22:24:03 +0200
Subject: [PATCH 05/21] Make input files for the benchmarks

---
 bench-run/inputs/apply.in                  | 1 +
 bench-run/inputs/{concat.txt => concat.in} | 0
 bench-run/inputs/cons.in                   | 1 +
 3 files changed, 2 insertions(+)
 create mode 100644 bench-run/inputs/apply.in
 rename bench-run/inputs/{concat.txt => concat.in} (100%)
 create mode 100644 bench-run/inputs/cons.in

diff --git a/bench-run/inputs/apply.in b/bench-run/inputs/apply.in
new file mode 100644
index 000000000000..3365fb5a87bb
--- /dev/null
+++ b/bench-run/inputs/apply.in
@@ -0,0 +1 @@
+sizeAndIndex:1 0,6 0,6 5,11 0,11 5,11 10,16 0,16 5,16 10,16 15,21 0,21 5,21 10,21 15,21 20,26 0,26 5,26 10,26 15,26 20,26 25,31 0,31 5,31 10,31 15,31 20,31 25,31 30
\ No newline at end of file
diff --git a/bench-run/inputs/concat.txt b/bench-run/inputs/concat.in
similarity index 100%
rename from bench-run/inputs/concat.txt
rename to bench-run/inputs/concat.in
diff --git a/bench-run/inputs/cons.in b/bench-run/inputs/cons.in
new file mode 100644
index 000000000000..87ca4f3dfd85
--- /dev/null
+++ b/bench-run/inputs/cons.in
@@ -0,0 +1 @@
+size:0,5,10,15,20,25,30
\ No newline at end of file

From c6a88e85dd4fd984bb674e88548ed6a03c7dbb9a Mon Sep 17 00:00:00 2001
From: Antoine Brunner <abrunner@lpdquatro4.epfl.ch>
Date: Wed, 2 Oct 2019 09:37:46 +0200
Subject: [PATCH 06/21] Add outputs of concat benchmarks

---
 bench-run/outputs/concat.csv | 295 +++++++++++++++++++++++++++++++++++
 1 file changed, 295 insertions(+)
 create mode 100644 bench-run/outputs/concat.csv

diff --git a/bench-run/outputs/concat.csv b/bench-run/outputs/concat.csv
new file mode 100644
index 000000000000..d8f32861f223
--- /dev/null
+++ b/bench-run/outputs/concat.csv
@@ -0,0 +1,295 @@
+"Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: sizes"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.488094,0.742509,"ns/op","0 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,37.246583,0.769948,"ns/op","0 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,37.821187,1.315976,"ns/op","0 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,38.490857,0.736351,"ns/op","0 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,40.290833,0.905165,"ns/op","0 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,39.535887,0.757934,"ns/op","0 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,40.654464,0.697325,"ns/op","0 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,27.289409,0.569568,"ns/op","5 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.301055,0.857886,"ns/op","5 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.521015,0.851255,"ns/op","5 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.573667,0.766589,"ns/op","5 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.770065,0.923906,"ns/op","5 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.759140,0.971084,"ns/op","5 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.450220,1.191643,"ns/op","5 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,27.438973,0.535034,"ns/op","10 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.526779,0.807807,"ns/op","10 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.829293,0.888853,"ns/op","10 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.641900,0.905702,"ns/op","10 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.723476,1.013583,"ns/op","10 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.421894,0.912429,"ns/op","10 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.630151,0.924153,"ns/op","10 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.162527,0.239812,"ns/op","15 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.569129,0.878811,"ns/op","15 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.829708,0.909951,"ns/op","15 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.800950,0.901774,"ns/op","15 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.581555,1.382670,"ns/op","15 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.787136,1.005488,"ns/op","15 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.795421,1.058560,"ns/op","15 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.334274,0.543448,"ns/op","20 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.566242,0.943875,"ns/op","20 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.697241,1.083458,"ns/op","20 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.990045,0.787530,"ns/op","20 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.861877,0.596299,"ns/op","20 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.928225,0.256207,"ns/op","20 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.276259,1.208086,"ns/op","20 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.614266,0.508494,"ns/op","25 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.440789,0.861255,"ns/op","25 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.812555,0.664966,"ns/op","25 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.748377,0.935177,"ns/op","25 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.663022,0.678699,"ns/op","25 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.467693,1.147664,"ns/op","25 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.103651,0.527903,"ns/op","25 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,29.837270,0.561916,"ns/op","30 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.168035,1.189375,"ns/op","30 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.167462,0.950895,"ns/op","30 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.683994,1.055132,"ns/op","30 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.795414,0.891281,"ns/op","30 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.152951,0.880661,"ns/op","30 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.933207,1.538616,"ns/op","30 30"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296916,0.002113,"ns/op","0 0"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297889,0.006059,"ns/op","0 5"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296278,0.000742,"ns/op","0 10"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296322,0.000758,"ns/op","0 15"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295653,0.000444,"ns/op","0 20"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295688,0.000749,"ns/op","0 25"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.299634,0.009849,"ns/op","0 30"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296299,0.000938,"ns/op","5 0"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297702,0.004775,"ns/op","5 5"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296138,0.000323,"ns/op","5 10"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295930,0.000644,"ns/op","5 15"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296391,0.000820,"ns/op","5 20"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296541,0.000922,"ns/op","5 25"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.298117,0.006964,"ns/op","5 30"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296104,0.001133,"ns/op","10 0"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295838,0.000420,"ns/op","10 5"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295459,0.000515,"ns/op","10 10"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295953,0.000451,"ns/op","10 15"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296068,0.000636,"ns/op","10 20"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296198,0.001034,"ns/op","10 25"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296534,0.001339,"ns/op","10 30"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296519,0.000608,"ns/op","15 0"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297473,0.002830,"ns/op","15 5"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296023,0.000684,"ns/op","15 10"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296294,0.000570,"ns/op","15 15"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296300,0.001330,"ns/op","15 20"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297613,0.003426,"ns/op","15 25"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.298608,0.007740,"ns/op","15 30"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296764,0.003618,"ns/op","20 0"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296218,0.000292,"ns/op","20 5"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295742,0.000416,"ns/op","20 10"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296667,0.001613,"ns/op","20 15"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297131,0.001928,"ns/op","20 20"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.302482,0.011770,"ns/op","20 25"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296503,0.000884,"ns/op","20 30"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295625,0.000324,"ns/op","25 0"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296373,0.001499,"ns/op","25 5"
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+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296889,0.001825,"ns/op","25 15"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.299895,0.009819,"ns/op","25 20"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296156,0.000342,"ns/op","25 25"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295917,0.000888,"ns/op","25 30"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296124,0.000532,"ns/op","30 0"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297129,0.002037,"ns/op","30 5"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296278,0.003101,"ns/op","30 10"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297238,0.002289,"ns/op","30 15"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296578,0.001398,"ns/op","30 20"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296667,0.002615,"ns/op","30 25"
+"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296790,0.001390,"ns/op","30 30"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,9.125775,0.026271,"ns/op","0 0"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,11.302720,0.305004,"ns/op","0 5"
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+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,11.225935,0.167463,"ns/op","5 0"
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+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,18.732598,0.538661,"ns/op","10 10"
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+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,31.902459,0.709423,"ns/op","10 20"
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+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,26.671230,0.564144,"ns/op","10 30"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,19.007867,0.297571,"ns/op","15 0"
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+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,30.424745,0.706044,"ns/op","15 15"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,37.012855,0.380740,"ns/op","15 20"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,31.043667,0.628859,"ns/op","15 25"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,32.737919,0.569340,"ns/op","15 30"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,24.852247,0.289149,"ns/op","20 0"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,28.146332,0.577450,"ns/op","20 5"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,31.253027,0.469309,"ns/op","20 10"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,37.423641,0.624641,"ns/op","20 15"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,42.680919,0.672108,"ns/op","20 20"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,36.628155,1.062099,"ns/op","20 25"
+"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,36.990993,0.807163,"ns/op","20 30"
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+"dotty.tools.benchmarks.tuples.Concat.toArray","avgt",1,20,44.433869,0.920946,"ns/op","30 15"
+"dotty.tools.benchmarks.tuples.Concat.toArray","avgt",1,20,118.928645,2.453709,"ns/op","30 20"
+"dotty.tools.benchmarks.tuples.Concat.toArray","avgt",1,20,31.861033,0.658809,"ns/op","30 25"
+"dotty.tools.benchmarks.tuples.Concat.toArray","avgt",1,20,35.703868,0.803278,"ns/op","30 30"

From e06a5f82473fd9dca217c7aee1b724e8bba7c24a Mon Sep 17 00:00:00 2001
From: Antoine Brunner <abrunner@lpdquatro4.epfl.ch>
Date: Wed, 2 Oct 2019 10:17:06 +0200
Subject: [PATCH 07/21] Add outputs of cons benchmarks

---
 bench-run/outputs/cons.csv | 29 +++++++++++++++++++++++++++++
 1 file changed, 29 insertions(+)
 create mode 100644 bench-run/outputs/cons.csv

diff --git a/bench-run/outputs/cons.csv b/bench-run/outputs/cons.csv
new file mode 100644
index 000000000000..bcc9f8593f28
--- /dev/null
+++ b/bench-run/outputs/cons.csv
@@ -0,0 +1,29 @@
+"Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: size"
+"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,23.593074,0.559760,"ns/op",0
+"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,23.126002,0.348034,"ns/op",5
+"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,22.677165,0.459156,"ns/op",10
+"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,24.910038,0.479292,"ns/op",15
+"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,25.165248,0.504894,"ns/op",20
+"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,25.241252,0.416694,"ns/op",25
+"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,27.782659,0.559301,"ns/op",30
+"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.298321,0.006222,"ns/op",0
+"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.296025,0.000850,"ns/op",5
+"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.299156,0.008331,"ns/op",10
+"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.296062,0.001481,"ns/op",15
+"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.296046,0.001143,"ns/op",20
+"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.308926,0.017358,"ns/op",25
+"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.306508,0.007257,"ns/op",30
+"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,4.738640,0.191935,"ns/op",0
+"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,69.176006,6.155676,"ns/op",5
+"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,88.832151,1.937672,"ns/op",10
+"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,116.252318,2.425801,"ns/op",15
+"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,87.405409,1.581465,"ns/op",20
+"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,49.311543,1.774938,"ns/op",25
+"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,55.203256,0.955310,"ns/op",30
+"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,4.739596,0.188809,"ns/op",0
+"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,63.384731,1.026435,"ns/op",5
+"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,90.589794,2.444226,"ns/op",10
+"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,116.843488,2.254244,"ns/op",15
+"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,86.216455,1.433045,"ns/op",20
+"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,49.051014,1.077130,"ns/op",25
+"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,55.671031,1.661106,"ns/op",30

From 109942c5737b348fcdaa14eb639c4b6c990e08a0 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <abrunner@lpdquatro4.epfl.ch>
Date: Wed, 2 Oct 2019 11:47:48 +0200
Subject: [PATCH 08/21] Add outputs of apply benchmarks

---
 bench-run/outputs/apply.csv | 85 +++++++++++++++++++++++++++++++++++++
 1 file changed, 85 insertions(+)
 create mode 100644 bench-run/outputs/apply.csv

diff --git a/bench-run/outputs/apply.csv b/bench-run/outputs/apply.csv
new file mode 100644
index 000000000000..7eb9219323cc
--- /dev/null
+++ b/bench-run/outputs/apply.csv
@@ -0,0 +1,85 @@
+"Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: sizeAndIndex"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.302796,0.003992,"ns/op","1 0"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.302248,0.004611,"ns/op","6 0"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.299675,0.004791,"ns/op","6 5"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.308888,0.006956,"ns/op","11 0"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.301277,0.003535,"ns/op","11 5"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.300426,0.003094,"ns/op","11 10"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.301387,0.002515,"ns/op","16 0"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.304609,0.005275,"ns/op","16 5"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.298971,0.003402,"ns/op","16 10"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.302746,0.005369,"ns/op","16 15"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.303780,0.004195,"ns/op","21 0"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.309071,0.006855,"ns/op","21 5"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.305058,0.005890,"ns/op","21 10"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.300222,0.002992,"ns/op","21 15"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.303375,0.005000,"ns/op","21 20"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.303624,0.006801,"ns/op","26 0"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.317166,0.007660,"ns/op","26 5"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.302866,0.002890,"ns/op","26 10"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.307574,0.006372,"ns/op","26 15"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.312211,0.008439,"ns/op","26 20"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.300770,0.004192,"ns/op","26 25"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.313411,0.008635,"ns/op","31 0"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.310805,0.007222,"ns/op","31 5"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.305519,0.006882,"ns/op","31 10"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.313372,0.009065,"ns/op","31 15"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.303700,0.005063,"ns/op","31 20"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.299757,0.002211,"ns/op","31 25"
+"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.298848,0.002455,"ns/op","31 30"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,3.706122,0.082386,"ns/op","1 0"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.206598,0.076812,"ns/op","6 0"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.027952,0.109764,"ns/op","6 5"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.628887,0.149810,"ns/op","11 0"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.322583,0.122501,"ns/op","11 5"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.260264,0.068996,"ns/op","11 10"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.502691,0.046695,"ns/op","16 0"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.225894,0.076483,"ns/op","16 5"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.491069,0.031204,"ns/op","16 10"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.179247,0.025271,"ns/op","16 15"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.577740,0.095874,"ns/op","21 0"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.340975,0.101002,"ns/op","21 5"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.549919,0.085750,"ns/op","21 10"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.220413,0.061036,"ns/op","21 15"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,3.903558,0.058349,"ns/op","21 20"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.202939,0.050177,"ns/op","26 0"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.200001,0.059330,"ns/op","26 5"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.198506,0.061250,"ns/op","26 10"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.205208,0.041869,"ns/op","26 15"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.198259,0.053616,"ns/op","26 20"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.257568,0.101048,"ns/op","26 25"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.225524,0.065781,"ns/op","31 0"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.204335,0.041007,"ns/op","31 5"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.254856,0.053846,"ns/op","31 10"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.204166,0.061426,"ns/op","31 15"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.253177,0.068150,"ns/op","31 20"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.418300,0.109917,"ns/op","31 25"
+"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.318239,0.108614,"ns/op","31 30"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,3.631052,0.067959,"ns/op","1 0"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.228909,0.104045,"ns/op","6 0"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,3.956169,0.085901,"ns/op","6 5"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.528560,0.067650,"ns/op","11 0"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.267749,0.121158,"ns/op","11 5"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.340369,0.094560,"ns/op","11 10"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.502422,0.058788,"ns/op","16 0"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.230764,0.054502,"ns/op","16 5"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.618353,0.103361,"ns/op","16 10"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.356611,0.120971,"ns/op","16 15"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.530590,0.053178,"ns/op","21 0"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.212605,0.053339,"ns/op","21 5"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.590118,0.083453,"ns/op","21 10"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.239007,0.107929,"ns/op","21 15"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,3.908145,0.050698,"ns/op","21 20"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.236628,0.071426,"ns/op","26 0"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.249880,0.081843,"ns/op","26 5"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.237230,0.077913,"ns/op","26 10"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.202678,0.051050,"ns/op","26 15"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.221350,0.087056,"ns/op","26 20"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.235956,0.078817,"ns/op","26 25"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.212674,0.056616,"ns/op","31 0"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.193940,0.058910,"ns/op","31 5"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.190698,0.044051,"ns/op","31 10"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.259565,0.117652,"ns/op","31 15"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.256121,0.073127,"ns/op","31 20"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.227038,0.062038,"ns/op","31 25"
+"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.220077,0.072770,"ns/op","31 30"

From 11c1d216a2387220a79986c7b805bafb5365a35a Mon Sep 17 00:00:00 2001
From: Antoine Brunner <abrunner@lpdquatro4.epfl.ch>
Date: Wed, 2 Oct 2019 14:04:36 +0200
Subject: [PATCH 09/21] Add inputs and outputs of arrayOps benchmark

---
 bench-run/inputs/arrayOps.in   |  1 +
 bench-run/outputs/arrayOps.csv | 36 ++++++++++++++++++++++++++++++++++
 2 files changed, 37 insertions(+)
 create mode 100644 bench-run/inputs/arrayOps.in
 create mode 100644 bench-run/outputs/arrayOps.csv

diff --git a/bench-run/inputs/arrayOps.in b/bench-run/inputs/arrayOps.in
new file mode 100644
index 000000000000..87ca4f3dfd85
--- /dev/null
+++ b/bench-run/inputs/arrayOps.in
@@ -0,0 +1 @@
+size:0,5,10,15,20,25,30
\ No newline at end of file
diff --git a/bench-run/outputs/arrayOps.csv b/bench-run/outputs/arrayOps.csv
new file mode 100644
index 000000000000..790ec38ff2c8
--- /dev/null
+++ b/bench-run/outputs/arrayOps.csv
@@ -0,0 +1,36 @@
+"Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: size"
+"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.301287,0.004558,"ns/op",0
+"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.302665,0.004649,"ns/op",5
+"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.305479,0.006833,"ns/op",10
+"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.307480,0.006484,"ns/op",15
+"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.301941,0.003893,"ns/op",20
+"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.300659,0.003699,"ns/op",25
+"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.304128,0.006872,"ns/op",30
+"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,4.807751,0.063805,"ns/op",0
+"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,7.383020,0.118580,"ns/op",5
+"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,9.542806,0.253861,"ns/op",10
+"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,15.847258,0.496734,"ns/op",15
+"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,21.553068,0.377783,"ns/op",20
+"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,17.307722,0.341839,"ns/op",25
+"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,19.259385,0.356215,"ns/op",30
+"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,5.133694,0.070668,"ns/op",0
+"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,7.675563,0.201592,"ns/op",5
+"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,10.634647,0.544432,"ns/op",10
+"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,15.733794,0.366517,"ns/op",15
+"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,21.311446,0.404450,"ns/op",20
+"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,5.102623,0.085603,"ns/op",25
+"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,5.118807,0.085698,"ns/op",30
+"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,3.258488,0.009474,"ns/op",0
+"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,9.559828,0.184920,"ns/op",5
+"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,22.830335,0.410024,"ns/op",10
+"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,32.244784,0.521161,"ns/op",15
+"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,51.550625,0.860758,"ns/op",20
+"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,14.909970,0.179355,"ns/op",25
+"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,16.811033,0.350358,"ns/op",30
+"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,3.258473,0.011320,"ns/op",0
+"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,9.570956,0.205092,"ns/op",5
+"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,22.768285,0.405557,"ns/op",10
+"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,34.880201,0.637106,"ns/op",15
+"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,51.613896,0.971396,"ns/op",20
+"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,3.846535,0.013833,"ns/op",25
+"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,3.856808,0.019754,"ns/op",30

From c3ded4fca1c3f8a1d15f37e1e405adac2dbfe0e8 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Fri, 4 Oct 2019 07:35:14 +0200
Subject: [PATCH 10/21] Shorten benchmark duration

---
 bench-run/src/main/scala/Main.scala | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/bench-run/src/main/scala/Main.scala b/bench-run/src/main/scala/Main.scala
index 6a937d4faf2b..2bb4855a2b68 100644
--- a/bench-run/src/main/scala/Main.scala
+++ b/bench-run/src/main/scala/Main.scala
@@ -2,9 +2,9 @@ package dotty.tools.benchmarks
 
 import org.openjdk.jmh.results.RunResult
 import org.openjdk.jmh.runner.Runner
-import org.openjdk.jmh.runner.options.OptionsBuilder
 import org.openjdk.jmh.annotations._
 import org.openjdk.jmh.results.format._
+import org.openjdk.jmh.runner.options._
 import java.util.concurrent.TimeUnit
 
 import scala.io.Source
@@ -13,7 +13,7 @@ object Bench {
   def main(args: Array[String]): Unit = {
     val (intArgs, args1) = args.span(x => try { x.toInt; true } catch { case _: Throwable => false } )
 
-    val warmup = if (intArgs.length > 0) intArgs(0).toInt else 30
+    val warmup = if (intArgs.length > 0) intArgs(0).toInt else 20
     val iterations = if (intArgs.length > 1) intArgs(1).toInt else 20
     val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
 
@@ -26,7 +26,9 @@ object Bench {
                .mode(Mode.AverageTime)
                .timeUnit(TimeUnit.NANOSECONDS)
                .warmupIterations(warmup)
+               .warmupTime(TimeValue.milliseconds(750))
                .measurementIterations(iterations)
+               .measurementTime(TimeValue.milliseconds(500))
                .forks(forks)
                .include(benchmarks)
                .resultFormat(ResultFormatType.CSV)

From 81849802dfea22d8eb3d0f9c5d1e395eb54e437c Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Sat, 5 Oct 2019 12:32:08 +0200
Subject: [PATCH 11/21] Made benchmarks more consistent and complete

---
 bench-run/src/main/scala/tuples/Apply.scala   | 11 +++----
 .../src/main/scala/tuples/ArrayOps.scala      | 16 ++++++----
 bench-run/src/main/scala/tuples/Concat.scala  | 24 +-------------
 bench-run/src/main/scala/tuples/Cons.scala    | 11 +------
 bench-run/src/main/scala/tuples/Tail.scala    | 32 +++++++++++++++++++
 5 files changed, 47 insertions(+), 47 deletions(-)
 create mode 100644 bench-run/src/main/scala/tuples/Tail.scala

diff --git a/bench-run/src/main/scala/tuples/Apply.scala b/bench-run/src/main/scala/tuples/Apply.scala
index 7df788cb2efc..06ea29711bf8 100644
--- a/bench-run/src/main/scala/tuples/Apply.scala
+++ b/bench-run/src/main/scala/tuples/Apply.scala
@@ -21,15 +21,12 @@ class Apply {
   }
 
   @Benchmark
-  def baseline(): Unit = {}
-
-  @Benchmark
-  def normal(): Any = {
-    tuple(index)
+  def tupleApply(): Any = {
+    DynamicTuple.dynamicApply(tuple, index)
   }
 
   @Benchmark
-  def inlined(): Any = {
-    DynamicTuple.dynamicApply(tuple, index)
+  def productElement(): Any = {
+    tuple.asInstanceOf[Product].productElement(index)
   }
 }
diff --git a/bench-run/src/main/scala/tuples/ArrayOps.scala b/bench-run/src/main/scala/tuples/ArrayOps.scala
index e14e1c996167..791bcbb5f14c 100644
--- a/bench-run/src/main/scala/tuples/ArrayOps.scala
+++ b/bench-run/src/main/scala/tuples/ArrayOps.scala
@@ -23,25 +23,27 @@ class ArrayOps {
   }
 
   @Benchmark
-  def baseline(): Unit = {}
-
-  @Benchmark
-  def toArray(): Array[Object] = {
+  def tupleToArray(): Array[Object] = {
     DynamicTuple.dynamicToArray(tuple)
   }
 
   @Benchmark
-  def toIArray(): IArray[Object] = {
+  def tupleToIArray(): IArray[Object] = {
     DynamicTuple.dynamicToIArray(tuple)
   }
 
   @Benchmark
-  def fromArray(): Tuple = {
+  def tupleFromArray(): Tuple = {
     DynamicTuple.dynamicFromArray(array)
   }
 
   @Benchmark
-  def fromIArray(): Tuple = {
+  def tupleFromIArray(): Tuple = {
     DynamicTuple.dynamicFromIArray(iarray)
   }
+
+  @Benchmark
+  def productToArray(): Array[Object] = {
+    DynamicTuple.productToArray(tuple.asInstanceOf[Product])
+  }
 }
diff --git a/bench-run/src/main/scala/tuples/Concat.scala b/bench-run/src/main/scala/tuples/Concat.scala
index 63b023322d4b..4f216f3db9d6 100644
--- a/bench-run/src/main/scala/tuples/Concat.scala
+++ b/bench-run/src/main/scala/tuples/Concat.scala
@@ -31,34 +31,12 @@ class Concat {
   }
 
   @Benchmark
-  def baseline(): Unit = {}
-
-  @Benchmark
-  def normal(): Tuple = {
-   tuple1 ++ tuple2
-  }
-
-  @Benchmark
-  def inlined(): Tuple = {
+  def tupleConcat(): Tuple = {
     DynamicTuple.dynamicConcat(tuple1, tuple2)
   }
 
-  // This part is here to try and measure the overhead of tranforming tuples to arrays, then concatenating
-  // the array, and then transforming back to a tuple
-  @Benchmark
-  def toArray(bh: Blackhole): Unit = {
-    bh.consume(DynamicTuple.dynamicToArray(tuple1))
-    bh.consume(DynamicTuple.dynamicToArray(tuple2))
-  }
-
   @Benchmark
   def arrayConcat(): Array[Object] = {
     array1 ++ array2
   }
-
-  @Benchmark
-  def fromArray(bh: Blackhole): Unit = {
-    bh.consume(DynamicTuple.dynamicFromArray[Tuple](array1))
-    bh.consume(DynamicTuple.dynamicFromArray[Tuple](array2))
-  }
 }
diff --git a/bench-run/src/main/scala/tuples/Cons.scala b/bench-run/src/main/scala/tuples/Cons.scala
index c5c68efcca1c..ea65e1dcf2ee 100644
--- a/bench-run/src/main/scala/tuples/Cons.scala
+++ b/bench-run/src/main/scala/tuples/Cons.scala
@@ -21,19 +21,10 @@ class Cons {
   }
 
   @Benchmark
-  def baseline(): Unit = {}
-
-  @Benchmark
-  def normal(): Tuple = {
-    "elem" *: tuple
-  }
-
-  @Benchmark
-  def inlined(): Tuple = {
+  def tupleCons(): Tuple = {
     DynamicTuple.dynamicCons("elem", tuple)
   }
 
-  // This part is here to measure the performance of dong a cons on arrays directly
   @Benchmark
   def arrayCons(): Array[Object] = {
     DynamicTuple.cons$Array("elem", array)
diff --git a/bench-run/src/main/scala/tuples/Tail.scala b/bench-run/src/main/scala/tuples/Tail.scala
new file mode 100644
index 000000000000..f685759b5989
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/Tail.scala
@@ -0,0 +1,32 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+import scala.runtime.DynamicTuple
+
+@State(Scope.Thread)
+class Tail {
+  @Param(Array("1"))
+  var size: Int = _
+  var tuple: NonEmptyTuple = _
+  var array: Array[Object] = _
+
+  @Setup
+  def setup(): Unit = {
+    tuple = "elem" *: ()
+
+    for (i <- 1 until size)
+      tuple = "elem" *: tuple
+
+    array = Array.fill(size)("elem")
+  }
+
+  @Benchmark
+  def tupleTail(): Tuple = {
+    DynamicTuple.dynamicTail(tuple)
+  }
+
+  @Benchmark
+  def arrayTail(): Array[Object] = {
+    array.tail
+  }
+}

From 4c348c15e3df11b8670e9ebc8fcc40a2710cc53c Mon Sep 17 00:00:00 2001
From: Antoine Brunner <abrunner@lpdquatro4.epfl.ch>
Date: Tue, 8 Oct 2019 21:38:24 +0200
Subject: [PATCH 12/21] Modify inputs

---
 bench-run/inputs/apply.in    |   2 +-
 bench-run/inputs/arrayOps.in |   2 +-
 bench-run/inputs/concat.in   |   2 +-
 bench-run/inputs/cons.in     |   2 +-
 bench-run/outputs/concat.csv | 392 +++++++++--------------------------
 5 files changed, 102 insertions(+), 298 deletions(-)
 mode change 100644 => 100755 bench-run/inputs/arrayOps.in
 mode change 100644 => 100755 bench-run/inputs/concat.in
 mode change 100644 => 100755 bench-run/inputs/cons.in

diff --git a/bench-run/inputs/apply.in b/bench-run/inputs/apply.in
index 3365fb5a87bb..905a73b537c9 100644
--- a/bench-run/inputs/apply.in
+++ b/bench-run/inputs/apply.in
@@ -1 +1 @@
-sizeAndIndex:1 0,6 0,6 5,11 0,11 5,11 10,16 0,16 5,16 10,16 15,21 0,21 5,21 10,21 15,21 20,26 0,26 5,26 10,26 15,26 20,26 25,31 0,31 5,31 10,31 15,31 20,31 25,31 30
\ No newline at end of file
+sizeAndIndex:20 0,20 1,20 2,20 3,20 4,20 5,20 6,20 7,20 8,20 9,20 10,20 11,20 12,20 13,20 14,20 15,20 16,20 17,20 18,20 19
diff --git a/bench-run/inputs/arrayOps.in b/bench-run/inputs/arrayOps.in
old mode 100644
new mode 100755
index 87ca4f3dfd85..058ba704b85b
--- a/bench-run/inputs/arrayOps.in
+++ b/bench-run/inputs/arrayOps.in
@@ -1 +1 @@
-size:0,5,10,15,20,25,30
\ No newline at end of file
+size:1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50
diff --git a/bench-run/inputs/concat.in b/bench-run/inputs/concat.in
old mode 100644
new mode 100755
index 7368b1fc8685..c6e774fd9412
--- a/bench-run/inputs/concat.in
+++ b/bench-run/inputs/concat.in
@@ -1 +1 @@
-sizes:0 0,0 5,0 10,0 15,0 20,0 25,0 30,5 0,5 5,5 10,5 15,5 20,5 25,5 30,10 0,10 5,10 10,10 15,10 20,10 25,10 30,15 0,15 5,15 10,15 15,15 20,15 25,15 30,20 0,20 5,20 10,20 15,20 20,20 25,20 30,25 0,25 5,25 10,25 15,25 20,25 25,25 30,30 0,30 5,30 10,30 15,30 20,30 25,30 30
\ No newline at end of file
+sizes:15 0,15 1,15 2,15 3,15 4,15 5,15 6,15 7,15 8,15 9,15 10,15 11,15 12,15 13,15 14,15 15,15 16,15 17,15 18,15 19,15 20,15 21,15 22,15 23,15 24,15 25,15 26,15 27,15 28,15 29,15 30,15 31,15 32,15 33,15 34,15 35,15 36,15 37,15 38,15 39,15 40,15 41,15 42,15 43,15 44,15 45,15 46,15 47,15 48,15 49,15 50
\ No newline at end of file
diff --git a/bench-run/inputs/cons.in b/bench-run/inputs/cons.in
old mode 100644
new mode 100755
index 87ca4f3dfd85..4555a56acbc3
--- a/bench-run/inputs/cons.in
+++ b/bench-run/inputs/cons.in
@@ -1 +1 @@
-size:0,5,10,15,20,25,30
\ No newline at end of file
+size:0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50
diff --git a/bench-run/outputs/concat.csv b/bench-run/outputs/concat.csv
index d8f32861f223..3c271b95f17f 100644
--- a/bench-run/outputs/concat.csv
+++ b/bench-run/outputs/concat.csv
@@ -1,295 +1,99 @@
 "Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: sizes"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.488094,0.742509,"ns/op","0 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,37.246583,0.769948,"ns/op","0 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,37.821187,1.315976,"ns/op","0 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,38.490857,0.736351,"ns/op","0 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,40.290833,0.905165,"ns/op","0 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,39.535887,0.757934,"ns/op","0 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,40.654464,0.697325,"ns/op","0 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,27.289409,0.569568,"ns/op","5 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.301055,0.857886,"ns/op","5 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.521015,0.851255,"ns/op","5 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.573667,0.766589,"ns/op","5 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.770065,0.923906,"ns/op","5 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.759140,0.971084,"ns/op","5 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.450220,1.191643,"ns/op","5 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,27.438973,0.535034,"ns/op","10 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.526779,0.807807,"ns/op","10 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.829293,0.888853,"ns/op","10 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.641900,0.905702,"ns/op","10 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.723476,1.013583,"ns/op","10 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.421894,0.912429,"ns/op","10 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.630151,0.924153,"ns/op","10 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.162527,0.239812,"ns/op","15 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.569129,0.878811,"ns/op","15 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.829708,0.909951,"ns/op","15 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.800950,0.901774,"ns/op","15 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.581555,1.382670,"ns/op","15 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.787136,1.005488,"ns/op","15 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.795421,1.058560,"ns/op","15 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.334274,0.543448,"ns/op","20 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.566242,0.943875,"ns/op","20 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.697241,1.083458,"ns/op","20 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.990045,0.787530,"ns/op","20 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.861877,0.596299,"ns/op","20 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.928225,0.256207,"ns/op","20 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.276259,1.208086,"ns/op","20 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.614266,0.508494,"ns/op","25 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.440789,0.861255,"ns/op","25 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.812555,0.664966,"ns/op","25 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.748377,0.935177,"ns/op","25 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.663022,0.678699,"ns/op","25 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.467693,1.147664,"ns/op","25 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.103651,0.527903,"ns/op","25 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,29.837270,0.561916,"ns/op","30 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.168035,1.189375,"ns/op","30 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.167462,0.950895,"ns/op","30 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.683994,1.055132,"ns/op","30 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.795414,0.891281,"ns/op","30 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.152951,0.880661,"ns/op","30 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.933207,1.538616,"ns/op","30 30"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296916,0.002113,"ns/op","0 0"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297889,0.006059,"ns/op","0 5"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296278,0.000742,"ns/op","0 10"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296322,0.000758,"ns/op","0 15"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295653,0.000444,"ns/op","0 20"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295688,0.000749,"ns/op","0 25"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.299634,0.009849,"ns/op","0 30"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296299,0.000938,"ns/op","5 0"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297702,0.004775,"ns/op","5 5"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296138,0.000323,"ns/op","5 10"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295930,0.000644,"ns/op","5 15"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296391,0.000820,"ns/op","5 20"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296541,0.000922,"ns/op","5 25"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.298117,0.006964,"ns/op","5 30"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296104,0.001133,"ns/op","10 0"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295838,0.000420,"ns/op","10 5"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295459,0.000515,"ns/op","10 10"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295953,0.000451,"ns/op","10 15"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296068,0.000636,"ns/op","10 20"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296198,0.001034,"ns/op","10 25"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296534,0.001339,"ns/op","10 30"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296519,0.000608,"ns/op","15 0"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297473,0.002830,"ns/op","15 5"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296023,0.000684,"ns/op","15 10"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296294,0.000570,"ns/op","15 15"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296300,0.001330,"ns/op","15 20"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297613,0.003426,"ns/op","15 25"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.298608,0.007740,"ns/op","15 30"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296764,0.003618,"ns/op","20 0"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296218,0.000292,"ns/op","20 5"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295742,0.000416,"ns/op","20 10"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296667,0.001613,"ns/op","20 15"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297131,0.001928,"ns/op","20 20"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.302482,0.011770,"ns/op","20 25"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296503,0.000884,"ns/op","20 30"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295625,0.000324,"ns/op","25 0"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296373,0.001499,"ns/op","25 5"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296215,0.001193,"ns/op","25 10"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296889,0.001825,"ns/op","25 15"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.299895,0.009819,"ns/op","25 20"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296156,0.000342,"ns/op","25 25"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.295917,0.000888,"ns/op","25 30"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296124,0.000532,"ns/op","30 0"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297129,0.002037,"ns/op","30 5"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296278,0.003101,"ns/op","30 10"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.297238,0.002289,"ns/op","30 15"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296578,0.001398,"ns/op","30 20"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296667,0.002615,"ns/op","30 25"
-"dotty.tools.benchmarks.tuples.Concat.baseline","avgt",1,20,0.296790,0.001390,"ns/op","30 30"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,9.125775,0.026271,"ns/op","0 0"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,11.302720,0.305004,"ns/op","0 5"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,13.412848,0.380257,"ns/op","0 10"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,18.794902,0.375087,"ns/op","0 15"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,24.346368,0.345869,"ns/op","0 20"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,20.259839,0.458558,"ns/op","0 25"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,21.207446,0.401497,"ns/op","0 30"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,11.225935,0.167463,"ns/op","5 0"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,14.658921,0.287129,"ns/op","5 5"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,16.168293,0.366947,"ns/op","5 10"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,23.160395,0.439607,"ns/op","5 15"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,27.848175,0.466669,"ns/op","5 20"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,23.722687,0.722341,"ns/op","5 25"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,24.796975,0.429540,"ns/op","5 30"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,13.683153,0.222650,"ns/op","10 0"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,16.539849,0.563490,"ns/op","10 5"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,18.732598,0.538661,"ns/op","10 10"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,24.185286,0.548354,"ns/op","10 15"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,31.902459,0.709423,"ns/op","10 20"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,24.986563,0.934148,"ns/op","10 25"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,26.671230,0.564144,"ns/op","10 30"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,19.007867,0.297571,"ns/op","15 0"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,22.436590,0.432366,"ns/op","15 5"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,24.228573,0.568284,"ns/op","15 10"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,30.424745,0.706044,"ns/op","15 15"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,37.012855,0.380740,"ns/op","15 20"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,31.043667,0.628859,"ns/op","15 25"
-"dotty.tools.benchmarks.tuples.Concat.fromArray","avgt",1,20,32.737919,0.569340,"ns/op","15 30"
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+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.968397,1.993173,"ns/op","5 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,27.762324,1.158246,"ns/op","10 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.876421,1.707638,"ns/op","10 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.791006,1.748622,"ns/op","10 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.908456,1.768426,"ns/op","10 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.054821,1.808581,"ns/op","10 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.921642,2.131137,"ns/op","10 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.935142,1.879981,"ns/op","10 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.703250,0.960906,"ns/op","15 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.568368,1.730140,"ns/op","15 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.508810,2.113427,"ns/op","15 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.874149,3.477187,"ns/op","15 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.911064,2.087707,"ns/op","15 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.335409,1.793512,"ns/op","15 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,50.205048,1.725805,"ns/op","15 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.567219,1.113097,"ns/op","20 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.123565,1.968626,"ns/op","20 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.838262,1.813011,"ns/op","20 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.709481,2.072816,"ns/op","20 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.265058,1.186582,"ns/op","20 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.820445,2.163612,"ns/op","20 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.070700,2.052776,"ns/op","20 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.729753,1.040504,"ns/op","25 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.074065,2.137299,"ns/op","25 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.431560,1.872455,"ns/op","25 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.178522,2.124893,"ns/op","25 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.855962,1.500332,"ns/op","25 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.220386,2.382938,"ns/op","25 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.287068,2.164299,"ns/op","25 30"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,29.816870,0.962122,"ns/op","30 0"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.951214,1.530499,"ns/op","30 5"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.470978,1.920687,"ns/op","30 10"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.810173,2.063265,"ns/op","30 15"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.413701,1.730144,"ns/op","30 20"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.213797,2.416549,"ns/op","30 25"
+"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.747754,2.456569,"ns/op","30 30"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.304691,0.007097,"ns/op","0 0"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,47.543050,1.662572,"ns/op","0 5"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,62.462817,1.743626,"ns/op","0 10"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,79.904105,3.126568,"ns/op","0 15"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,101.344998,3.555549,"ns/op","0 20"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,59.063976,2.283685,"ns/op","0 25"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,63.392042,2.709558,"ns/op","0 30"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.317980,0.020179,"ns/op","5 0"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,47.378968,1.532791,"ns/op","5 5"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,123.313153,4.442324,"ns/op","5 10"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,136.692050,5.550220,"ns/op","5 15"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,158.265492,5.657457,"ns/op","5 20"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,73.651463,3.240342,"ns/op","5 25"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,77.594386,3.172696,"ns/op","5 30"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.322615,0.022144,"ns/op","10 0"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,118.205921,5.312860,"ns/op","10 5"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,88.383479,3.147018,"ns/op","10 10"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,149.609022,6.238933,"ns/op","10 15"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,183.818928,6.719115,"ns/op","10 20"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,91.901040,2.109444,"ns/op","10 25"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,94.624579,3.655768,"ns/op","10 30"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.315289,0.018805,"ns/op","15 0"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,135.598326,5.364097,"ns/op","15 5"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,142.985946,5.606795,"ns/op","15 10"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,112.257985,4.611035,"ns/op","15 15"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,273.191448,8.190918,"ns/op","15 20"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,141.724634,4.793305,"ns/op","15 25"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,147.844540,6.074874,"ns/op","15 30"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.311072,0.014647,"ns/op","20 0"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,147.014190,5.872156,"ns/op","20 5"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,166.750133,6.565463,"ns/op","20 10"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,171.776098,1.679049,"ns/op","20 15"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,169.323782,5.904121,"ns/op","20 20"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,172.999232,3.614311,"ns/op","20 25"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,175.851694,7.167824,"ns/op","20 30"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.314175,0.018472,"ns/op","25 0"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,74.955726,3.718710,"ns/op","25 5"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,92.127105,3.890740,"ns/op","25 10"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,139.406052,11.825064,"ns/op","25 15"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,171.993213,7.954011,"ns/op","25 20"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,90.590646,3.574160,"ns/op","25 25"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,94.871603,1.402416,"ns/op","25 30"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.306027,0.005600,"ns/op","30 0"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,77.015210,3.415035,"ns/op","30 5"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,90.806275,3.880782,"ns/op","30 10"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,106.207263,3.900260,"ns/op","30 15"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,169.520545,6.094742,"ns/op","30 20"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,95.912146,3.732152,"ns/op","30 25"
+"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,102.197442,3.626954,"ns/op","30 30"

From 38e4fbd181811453097505e734c2b21137756c48 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Tue, 8 Oct 2019 21:43:05 +0200
Subject: [PATCH 13/21] Add some missing benchmarks

---
 bench-run/src/main/scala/tuples/ArrayOps.scala | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/bench-run/src/main/scala/tuples/ArrayOps.scala b/bench-run/src/main/scala/tuples/ArrayOps.scala
index 791bcbb5f14c..bef4a99a3d46 100644
--- a/bench-run/src/main/scala/tuples/ArrayOps.scala
+++ b/bench-run/src/main/scala/tuples/ArrayOps.scala
@@ -5,7 +5,7 @@ import scala.runtime.DynamicTuple
 
 @State(Scope.Thread)
 class ArrayOps {
-  @Param(Array("0"))
+  @Param(Array("1"))
   var size: Int = _
   var tuple: Tuple = _
   var array: Array[Object] = _
@@ -46,4 +46,9 @@ class ArrayOps {
   def productToArray(): Array[Object] = {
     DynamicTuple.productToArray(tuple.asInstanceOf[Product])
   }
+
+  @Benchmark
+  def cloneArray(): Array[Object] = {
+    array.clone()
+  }
 }

From a5a6fe944f17ed02115ecd7ee1dd5b9a9c73e8f6 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Wed, 16 Oct 2019 14:41:08 +0200
Subject: [PATCH 14/21] Add global benchmark on tuples

---
 .../src/main/scala/tuples/TupleOps.scala      | 46 +++++++++++++++++++
 1 file changed, 46 insertions(+)
 create mode 100644 bench-run/src/main/scala/tuples/TupleOps.scala

diff --git a/bench-run/src/main/scala/tuples/TupleOps.scala b/bench-run/src/main/scala/tuples/TupleOps.scala
new file mode 100644
index 000000000000..a4c1d2d08ee3
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/TupleOps.scala
@@ -0,0 +1,46 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+
+@State(Scope.Thread)
+class TupleOps {
+  var tuple1: Tuple = _
+  var tuple2: Tuple = _
+
+  @Setup
+  def setup(): Unit = {
+    tuple1 = ()
+    for (i <- 1 until 15)
+      tuple1 = s"elem$i" *: tuple1
+
+    tuple2 = ()
+    for (i <- 1 until 10)
+      tuple2 = s"elem$i" *: tuple2
+  }
+
+  def tupleFlatMap(tuple: Tuple, f: [A] => A => Tuple): Tuple = {
+    def tailRecFlatMap(t: Tuple, acc: Tuple): Tuple = t match {
+      case () => acc
+      case x *: rest => tailRecFlatMap(rest, acc ++ f(x))
+    }
+    tailRecFlatMap(tuple, ())
+  }
+
+  def tupleReverse(tuple: Tuple): Tuple = {
+    def tailRecReverse(t: Tuple, acc: Tuple): Tuple = t match {
+      case () => acc
+      case x *: rest => tailRecReverse(rest, x *: acc)
+    }
+    tailRecReverse(tuple, ())
+  }
+
+  @Benchmark
+  def reverse(): Tuple = {
+    tupleReverse(tuple1)
+  }
+
+  @Benchmark
+  def flatMap(): Tuple = {
+    tupleFlatMap(tuple2, [A] => (x: A) => (x, x))
+  }
+}

From 05c0c954d80c85f3ced2e61a3f8fbee651a689cc Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Thu, 17 Oct 2019 22:15:17 +0200
Subject: [PATCH 15/21] Change benchmarks input format

---
 bench-run/src/main/scala/Main.scala | 37 ++++++++++++++++-------------
 1 file changed, 21 insertions(+), 16 deletions(-)

diff --git a/bench-run/src/main/scala/Main.scala b/bench-run/src/main/scala/Main.scala
index 2bb4855a2b68..ad102078b5b3 100644
--- a/bench-run/src/main/scala/Main.scala
+++ b/bench-run/src/main/scala/Main.scala
@@ -17,28 +17,33 @@ object Bench {
     val iterations = if (intArgs.length > 1) intArgs(1).toInt else 20
     val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
 
-    val benchmarks = if (args1.length > 0) args1(0) else ".*"
-    val outputFile = if (args1.length > 2) args1(2) else "output.csv"
+    if (args1.isEmpty) {
+      println("You should specify which benchmarks to run.")
+      return
+    }
 
     var builder = new OptionsBuilder()
-               .shouldFailOnError(true)
-               .jvmArgs("-Xms2G", "-Xmx2G")
-               .mode(Mode.AverageTime)
-               .timeUnit(TimeUnit.NANOSECONDS)
-               .warmupIterations(warmup)
-               .warmupTime(TimeValue.milliseconds(750))
-               .measurementIterations(iterations)
-               .measurementTime(TimeValue.milliseconds(500))
-               .forks(forks)
-               .include(benchmarks)
-               .resultFormat(ResultFormatType.CSV)
-               .result(outputFile)
-
-    if (args1.length > 1) {
+      .shouldFailOnError(true)
+      .jvmArgs("-Xms2G", "-Xmx2G")
+      .mode(Mode.AverageTime)
+      .timeUnit(TimeUnit.NANOSECONDS)
+      .warmupIterations(warmup)
+      .warmupTime(TimeValue.milliseconds(750))
+      .measurementIterations(iterations)
+      .measurementTime(TimeValue.milliseconds(500))
+      .forks(forks)
+      .include(args1(0))
+      .resultFormat(ResultFormatType.CSV)
+
+    if (args1.length > 1 && args1(1) != "--") {
       for ((param, values) <- paramsFromFile(args1(1)))
         builder = builder.param(param, values: _*)
     }
 
+    if (args1.length > 2) {
+      builder = builder.result(args1(2))
+    }
+
     val runner = new Runner(builder.build) // full access to all JMH features, you can also provide a custom output Format here
     runner.run // actually run the benchmarks
   }

From a011faf3cbbf840daf9c132a13ba8c1a31a33f20 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <abrunner@lpdquatro4.epfl.ch>
Date: Thu, 31 Oct 2019 16:32:46 +0100
Subject: [PATCH 16/21] Renamed the input files for consistency

---
 bench-run/inputs/{arrayOps.in => conversions.in} | 0
 bench-run/inputs/tail.in                         | 1 +
 2 files changed, 1 insertion(+)
 rename bench-run/inputs/{arrayOps.in => conversions.in} (100%)
 create mode 100755 bench-run/inputs/tail.in

diff --git a/bench-run/inputs/arrayOps.in b/bench-run/inputs/conversions.in
similarity index 100%
rename from bench-run/inputs/arrayOps.in
rename to bench-run/inputs/conversions.in
diff --git a/bench-run/inputs/tail.in b/bench-run/inputs/tail.in
new file mode 100755
index 000000000000..058ba704b85b
--- /dev/null
+++ b/bench-run/inputs/tail.in
@@ -0,0 +1 @@
+size:1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50

From f9bbdcbaec6d28538d7c3d882a21229e9a8d0e86 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Mon, 11 Nov 2019 22:10:38 +0100
Subject: [PATCH 17/21] Add benchmarks for map and zip

---
 bench-run/inputs/map.in                   |  1 +
 bench-run/inputs/zip.in                   |  1 +
 bench-run/outputs/apply.csv               | 85 -------------------
 bench-run/outputs/arrayOps.csv            | 36 ---------
 bench-run/outputs/concat.csv              | 99 -----------------------
 bench-run/outputs/cons.csv                | 29 -------
 bench-run/src/main/scala/tuples/Map.scala | 40 +++++++++
 bench-run/src/main/scala/tuples/Zip.scala | 38 +++++++++
 8 files changed, 80 insertions(+), 249 deletions(-)
 create mode 100644 bench-run/inputs/map.in
 create mode 100644 bench-run/inputs/zip.in
 delete mode 100644 bench-run/outputs/apply.csv
 delete mode 100644 bench-run/outputs/arrayOps.csv
 delete mode 100644 bench-run/outputs/concat.csv
 delete mode 100644 bench-run/outputs/cons.csv
 create mode 100644 bench-run/src/main/scala/tuples/Map.scala
 create mode 100644 bench-run/src/main/scala/tuples/Zip.scala

diff --git a/bench-run/inputs/map.in b/bench-run/inputs/map.in
new file mode 100644
index 000000000000..4555a56acbc3
--- /dev/null
+++ b/bench-run/inputs/map.in
@@ -0,0 +1 @@
+size:0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50
diff --git a/bench-run/inputs/zip.in b/bench-run/inputs/zip.in
new file mode 100644
index 000000000000..4555a56acbc3
--- /dev/null
+++ b/bench-run/inputs/zip.in
@@ -0,0 +1 @@
+size:0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50
diff --git a/bench-run/outputs/apply.csv b/bench-run/outputs/apply.csv
deleted file mode 100644
index 7eb9219323cc..000000000000
--- a/bench-run/outputs/apply.csv
+++ /dev/null
@@ -1,85 +0,0 @@
-"Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: sizeAndIndex"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.302796,0.003992,"ns/op","1 0"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.302248,0.004611,"ns/op","6 0"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.299675,0.004791,"ns/op","6 5"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.308888,0.006956,"ns/op","11 0"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.301277,0.003535,"ns/op","11 5"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.300426,0.003094,"ns/op","11 10"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.301387,0.002515,"ns/op","16 0"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.304609,0.005275,"ns/op","16 5"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.298971,0.003402,"ns/op","16 10"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.302746,0.005369,"ns/op","16 15"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.303780,0.004195,"ns/op","21 0"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.309071,0.006855,"ns/op","21 5"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.305058,0.005890,"ns/op","21 10"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.300222,0.002992,"ns/op","21 15"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.303375,0.005000,"ns/op","21 20"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.303624,0.006801,"ns/op","26 0"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.317166,0.007660,"ns/op","26 5"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.302866,0.002890,"ns/op","26 10"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.307574,0.006372,"ns/op","26 15"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.312211,0.008439,"ns/op","26 20"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.300770,0.004192,"ns/op","26 25"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.313411,0.008635,"ns/op","31 0"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.310805,0.007222,"ns/op","31 5"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.305519,0.006882,"ns/op","31 10"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.313372,0.009065,"ns/op","31 15"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.303700,0.005063,"ns/op","31 20"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.299757,0.002211,"ns/op","31 25"
-"dotty.tools.benchmarks.tuples.Apply.baseline","avgt",1,20,0.298848,0.002455,"ns/op","31 30"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,3.706122,0.082386,"ns/op","1 0"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.206598,0.076812,"ns/op","6 0"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.027952,0.109764,"ns/op","6 5"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.628887,0.149810,"ns/op","11 0"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.322583,0.122501,"ns/op","11 5"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.260264,0.068996,"ns/op","11 10"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.502691,0.046695,"ns/op","16 0"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.225894,0.076483,"ns/op","16 5"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.491069,0.031204,"ns/op","16 10"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.179247,0.025271,"ns/op","16 15"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.577740,0.095874,"ns/op","21 0"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.340975,0.101002,"ns/op","21 5"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.549919,0.085750,"ns/op","21 10"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.220413,0.061036,"ns/op","21 15"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,3.903558,0.058349,"ns/op","21 20"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.202939,0.050177,"ns/op","26 0"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.200001,0.059330,"ns/op","26 5"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.198506,0.061250,"ns/op","26 10"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.205208,0.041869,"ns/op","26 15"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.198259,0.053616,"ns/op","26 20"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.257568,0.101048,"ns/op","26 25"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.225524,0.065781,"ns/op","31 0"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.204335,0.041007,"ns/op","31 5"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.254856,0.053846,"ns/op","31 10"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.204166,0.061426,"ns/op","31 15"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.253177,0.068150,"ns/op","31 20"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.418300,0.109917,"ns/op","31 25"
-"dotty.tools.benchmarks.tuples.Apply.inlined","avgt",1,20,4.318239,0.108614,"ns/op","31 30"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,3.631052,0.067959,"ns/op","1 0"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.228909,0.104045,"ns/op","6 0"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,3.956169,0.085901,"ns/op","6 5"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.528560,0.067650,"ns/op","11 0"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.267749,0.121158,"ns/op","11 5"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.340369,0.094560,"ns/op","11 10"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.502422,0.058788,"ns/op","16 0"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.230764,0.054502,"ns/op","16 5"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.618353,0.103361,"ns/op","16 10"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.356611,0.120971,"ns/op","16 15"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.530590,0.053178,"ns/op","21 0"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.212605,0.053339,"ns/op","21 5"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.590118,0.083453,"ns/op","21 10"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.239007,0.107929,"ns/op","21 15"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,3.908145,0.050698,"ns/op","21 20"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.236628,0.071426,"ns/op","26 0"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.249880,0.081843,"ns/op","26 5"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.237230,0.077913,"ns/op","26 10"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.202678,0.051050,"ns/op","26 15"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.221350,0.087056,"ns/op","26 20"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.235956,0.078817,"ns/op","26 25"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.212674,0.056616,"ns/op","31 0"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.193940,0.058910,"ns/op","31 5"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.190698,0.044051,"ns/op","31 10"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.259565,0.117652,"ns/op","31 15"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.256121,0.073127,"ns/op","31 20"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.227038,0.062038,"ns/op","31 25"
-"dotty.tools.benchmarks.tuples.Apply.normal","avgt",1,20,4.220077,0.072770,"ns/op","31 30"
diff --git a/bench-run/outputs/arrayOps.csv b/bench-run/outputs/arrayOps.csv
deleted file mode 100644
index 790ec38ff2c8..000000000000
--- a/bench-run/outputs/arrayOps.csv
+++ /dev/null
@@ -1,36 +0,0 @@
-"Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: size"
-"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.301287,0.004558,"ns/op",0
-"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.302665,0.004649,"ns/op",5
-"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.305479,0.006833,"ns/op",10
-"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.307480,0.006484,"ns/op",15
-"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.301941,0.003893,"ns/op",20
-"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.300659,0.003699,"ns/op",25
-"dotty.tools.benchmarks.tuples.ArrayOps.baseline","avgt",1,20,0.304128,0.006872,"ns/op",30
-"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,4.807751,0.063805,"ns/op",0
-"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,7.383020,0.118580,"ns/op",5
-"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,9.542806,0.253861,"ns/op",10
-"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,15.847258,0.496734,"ns/op",15
-"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,21.553068,0.377783,"ns/op",20
-"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,17.307722,0.341839,"ns/op",25
-"dotty.tools.benchmarks.tuples.ArrayOps.fromArray","avgt",1,20,19.259385,0.356215,"ns/op",30
-"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,5.133694,0.070668,"ns/op",0
-"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,7.675563,0.201592,"ns/op",5
-"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,10.634647,0.544432,"ns/op",10
-"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,15.733794,0.366517,"ns/op",15
-"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,21.311446,0.404450,"ns/op",20
-"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,5.102623,0.085603,"ns/op",25
-"dotty.tools.benchmarks.tuples.ArrayOps.fromIArray","avgt",1,20,5.118807,0.085698,"ns/op",30
-"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,3.258488,0.009474,"ns/op",0
-"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,9.559828,0.184920,"ns/op",5
-"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,22.830335,0.410024,"ns/op",10
-"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,32.244784,0.521161,"ns/op",15
-"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,51.550625,0.860758,"ns/op",20
-"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,14.909970,0.179355,"ns/op",25
-"dotty.tools.benchmarks.tuples.ArrayOps.toArray","avgt",1,20,16.811033,0.350358,"ns/op",30
-"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,3.258473,0.011320,"ns/op",0
-"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,9.570956,0.205092,"ns/op",5
-"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,22.768285,0.405557,"ns/op",10
-"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,34.880201,0.637106,"ns/op",15
-"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,51.613896,0.971396,"ns/op",20
-"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,3.846535,0.013833,"ns/op",25
-"dotty.tools.benchmarks.tuples.ArrayOps.toIArray","avgt",1,20,3.856808,0.019754,"ns/op",30
diff --git a/bench-run/outputs/concat.csv b/bench-run/outputs/concat.csv
deleted file mode 100644
index 3c271b95f17f..000000000000
--- a/bench-run/outputs/concat.csv
+++ /dev/null
@@ -1,99 +0,0 @@
-"Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: sizes"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,38.909750,0.738950,"ns/op","0 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,36.819358,0.152812,"ns/op","0 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,37.769272,1.342357,"ns/op","0 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,39.073530,1.396754,"ns/op","0 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,39.396242,1.421824,"ns/op","0 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,40.218793,1.726922,"ns/op","0 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,40.909185,1.635656,"ns/op","0 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,27.462873,1.081689,"ns/op","5 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.722235,1.858725,"ns/op","5 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.990633,1.774447,"ns/op","5 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.037318,1.994271,"ns/op","5 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.429481,1.752596,"ns/op","5 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.418024,2.339706,"ns/op","5 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.968397,1.993173,"ns/op","5 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,27.762324,1.158246,"ns/op","10 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,43.876421,1.707638,"ns/op","10 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.791006,1.748622,"ns/op","10 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.908456,1.768426,"ns/op","10 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.054821,1.808581,"ns/op","10 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.921642,2.131137,"ns/op","10 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.935142,1.879981,"ns/op","10 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.703250,0.960906,"ns/op","15 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.568368,1.730140,"ns/op","15 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.508810,2.113427,"ns/op","15 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.874149,3.477187,"ns/op","15 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.911064,2.087707,"ns/op","15 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.335409,1.793512,"ns/op","15 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,50.205048,1.725805,"ns/op","15 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.567219,1.113097,"ns/op","20 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.123565,1.968626,"ns/op","20 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,44.838262,1.813011,"ns/op","20 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.709481,2.072816,"ns/op","20 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.265058,1.186582,"ns/op","20 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.820445,2.163612,"ns/op","20 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.070700,2.052776,"ns/op","20 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,28.729753,1.040504,"ns/op","25 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.074065,2.137299,"ns/op","25 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.431560,1.872455,"ns/op","25 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.178522,2.124893,"ns/op","25 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,47.855962,1.500332,"ns/op","25 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.220386,2.382938,"ns/op","25 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.287068,2.164299,"ns/op","25 30"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,29.816870,0.962122,"ns/op","30 0"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,45.951214,1.530499,"ns/op","30 5"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,46.470978,1.920687,"ns/op","30 10"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.810173,2.063265,"ns/op","30 15"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.413701,1.730144,"ns/op","30 20"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,48.213797,2.416549,"ns/op","30 25"
-"dotty.tools.benchmarks.tuples.Concat.arrayConcat","avgt",1,20,49.747754,2.456569,"ns/op","30 30"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.304691,0.007097,"ns/op","0 0"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,47.543050,1.662572,"ns/op","0 5"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,62.462817,1.743626,"ns/op","0 10"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,79.904105,3.126568,"ns/op","0 15"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,101.344998,3.555549,"ns/op","0 20"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,59.063976,2.283685,"ns/op","0 25"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,63.392042,2.709558,"ns/op","0 30"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.317980,0.020179,"ns/op","5 0"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,47.378968,1.532791,"ns/op","5 5"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,123.313153,4.442324,"ns/op","5 10"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,136.692050,5.550220,"ns/op","5 15"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,158.265492,5.657457,"ns/op","5 20"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,73.651463,3.240342,"ns/op","5 25"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,77.594386,3.172696,"ns/op","5 30"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.322615,0.022144,"ns/op","10 0"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,118.205921,5.312860,"ns/op","10 5"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,88.383479,3.147018,"ns/op","10 10"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,149.609022,6.238933,"ns/op","10 15"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,183.818928,6.719115,"ns/op","10 20"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,91.901040,2.109444,"ns/op","10 25"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,94.624579,3.655768,"ns/op","10 30"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.315289,0.018805,"ns/op","15 0"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,135.598326,5.364097,"ns/op","15 5"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,142.985946,5.606795,"ns/op","15 10"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,112.257985,4.611035,"ns/op","15 15"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,273.191448,8.190918,"ns/op","15 20"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,141.724634,4.793305,"ns/op","15 25"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,147.844540,6.074874,"ns/op","15 30"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.311072,0.014647,"ns/op","20 0"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,147.014190,5.872156,"ns/op","20 5"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,166.750133,6.565463,"ns/op","20 10"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,171.776098,1.679049,"ns/op","20 15"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,169.323782,5.904121,"ns/op","20 20"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,172.999232,3.614311,"ns/op","20 25"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,175.851694,7.167824,"ns/op","20 30"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.314175,0.018472,"ns/op","25 0"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,74.955726,3.718710,"ns/op","25 5"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,92.127105,3.890740,"ns/op","25 10"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,139.406052,11.825064,"ns/op","25 15"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,171.993213,7.954011,"ns/op","25 20"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,90.590646,3.574160,"ns/op","25 25"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,94.871603,1.402416,"ns/op","25 30"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,3.306027,0.005600,"ns/op","30 0"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,77.015210,3.415035,"ns/op","30 5"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,90.806275,3.880782,"ns/op","30 10"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,106.207263,3.900260,"ns/op","30 15"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,169.520545,6.094742,"ns/op","30 20"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,95.912146,3.732152,"ns/op","30 25"
-"dotty.tools.benchmarks.tuples.Concat.tupleConcat","avgt",1,20,102.197442,3.626954,"ns/op","30 30"
diff --git a/bench-run/outputs/cons.csv b/bench-run/outputs/cons.csv
deleted file mode 100644
index bcc9f8593f28..000000000000
--- a/bench-run/outputs/cons.csv
+++ /dev/null
@@ -1,29 +0,0 @@
-"Benchmark","Mode","Threads","Samples","Score","Score Error (99.9%)","Unit","Param: size"
-"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,23.593074,0.559760,"ns/op",0
-"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,23.126002,0.348034,"ns/op",5
-"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,22.677165,0.459156,"ns/op",10
-"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,24.910038,0.479292,"ns/op",15
-"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,25.165248,0.504894,"ns/op",20
-"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,25.241252,0.416694,"ns/op",25
-"dotty.tools.benchmarks.tuples.Cons.arrayCons","avgt",1,20,27.782659,0.559301,"ns/op",30
-"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.298321,0.006222,"ns/op",0
-"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.296025,0.000850,"ns/op",5
-"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.299156,0.008331,"ns/op",10
-"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.296062,0.001481,"ns/op",15
-"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.296046,0.001143,"ns/op",20
-"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.308926,0.017358,"ns/op",25
-"dotty.tools.benchmarks.tuples.Cons.baseline","avgt",1,20,0.306508,0.007257,"ns/op",30
-"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,4.738640,0.191935,"ns/op",0
-"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,69.176006,6.155676,"ns/op",5
-"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,88.832151,1.937672,"ns/op",10
-"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,116.252318,2.425801,"ns/op",15
-"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,87.405409,1.581465,"ns/op",20
-"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,49.311543,1.774938,"ns/op",25
-"dotty.tools.benchmarks.tuples.Cons.inlined","avgt",1,20,55.203256,0.955310,"ns/op",30
-"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,4.739596,0.188809,"ns/op",0
-"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,63.384731,1.026435,"ns/op",5
-"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,90.589794,2.444226,"ns/op",10
-"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,116.843488,2.254244,"ns/op",15
-"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,86.216455,1.433045,"ns/op",20
-"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,49.051014,1.077130,"ns/op",25
-"dotty.tools.benchmarks.tuples.Cons.normal","avgt",1,20,55.671031,1.661106,"ns/op",30
diff --git a/bench-run/src/main/scala/tuples/Map.scala b/bench-run/src/main/scala/tuples/Map.scala
new file mode 100644
index 000000000000..9b3807355087
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/Map.scala
@@ -0,0 +1,40 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+import scala.runtime.DynamicTuple
+
+@State(Scope.Thread)
+class Map {
+  @Param(Array("0"))
+  var size: Int = _
+  var tuple: Tuple = _
+  var array: Array[Object] = _
+
+  @Setup
+  def setup(): Unit = {
+    tuple = ()
+
+    for (i <- 1 to size)
+      tuple = "elem" *: tuple
+
+    array = Array.fill(size)("elem")
+  }
+
+  def f: PolyFunction = new PolyFunction {
+    def apply[T](x: T): T = {
+      x.asInstanceOf[String].updated(0, 'a').asInstanceOf[T]
+    }
+  }
+
+  type Id[X] = X
+
+  @Benchmark
+  def tupleMap(): Tuple = {
+    DynamicTuple.dynamicMap[Tuple, Id](tuple, [T] => (x:T) => x.asInstanceOf[String].updated(0, 'a').asInstanceOf[T])
+  }
+
+  @Benchmark
+  def arrayMap(): Array[Object] = {
+    array.map(x => x.asInstanceOf[String].updated(0, 'a'))
+  }
+}
diff --git a/bench-run/src/main/scala/tuples/Zip.scala b/bench-run/src/main/scala/tuples/Zip.scala
new file mode 100644
index 000000000000..1b95922a01f9
--- /dev/null
+++ b/bench-run/src/main/scala/tuples/Zip.scala
@@ -0,0 +1,38 @@
+package dotty.tools.benchmarks.tuples
+
+import org.openjdk.jmh.annotations._
+import scala.runtime.DynamicTuple
+
+@State(Scope.Thread)
+class Zip {
+  @Param(Array("0"))
+  var size: Int = _
+  var tuple1: Tuple = _
+  var tuple2: Tuple = _
+  var array1: Array[Object] = _
+  var array2: Array[Object] = _
+
+  @Setup
+  def setup(): Unit = {
+    tuple1 = ()
+    tuple2 = ()
+
+    for (i <- 1 to size) {
+      tuple1 = "el" *: tuple1
+      tuple2 = "em" *: tuple2
+    }
+
+    array1 = Array.fill(size)("el")
+    array2 = Array.fill(size)("em")
+  }
+
+  @Benchmark
+  def tupleZip(): Tuple = {
+    DynamicTuple.dynamicZip(tuple1, tuple2)
+  }
+
+  @Benchmark
+  def arrayZip(): Array[(Object, Object)] = {
+    array1.zip(array2)
+  }
+}

From 358ea0e3a73abc9a97169ffe3724b36f4acc1b39 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Wed, 20 Nov 2019 21:33:25 +0100
Subject: [PATCH 18/21] Add help message for bench-run

---
 bench-run/inputs/{ => tuples}/apply.in       |  0
 bench-run/inputs/{ => tuples}/concat.in      |  0
 bench-run/inputs/{ => tuples}/cons.in        |  0
 bench-run/inputs/{ => tuples}/conversions.in |  0
 bench-run/inputs/{ => tuples}/map.in         |  0
 bench-run/inputs/{ => tuples}/tail.in        |  0
 bench-run/inputs/{ => tuples}/zip.in         |  0
 bench-run/src/main/scala/Main.scala          | 29 +++++++++++++++++---
 8 files changed, 25 insertions(+), 4 deletions(-)
 rename bench-run/inputs/{ => tuples}/apply.in (100%)
 rename bench-run/inputs/{ => tuples}/concat.in (100%)
 mode change 100755 => 100644
 rename bench-run/inputs/{ => tuples}/cons.in (100%)
 mode change 100755 => 100644
 rename bench-run/inputs/{ => tuples}/conversions.in (100%)
 mode change 100755 => 100644
 rename bench-run/inputs/{ => tuples}/map.in (100%)
 rename bench-run/inputs/{ => tuples}/tail.in (100%)
 mode change 100755 => 100644
 rename bench-run/inputs/{ => tuples}/zip.in (100%)

diff --git a/bench-run/inputs/apply.in b/bench-run/inputs/tuples/apply.in
similarity index 100%
rename from bench-run/inputs/apply.in
rename to bench-run/inputs/tuples/apply.in
diff --git a/bench-run/inputs/concat.in b/bench-run/inputs/tuples/concat.in
old mode 100755
new mode 100644
similarity index 100%
rename from bench-run/inputs/concat.in
rename to bench-run/inputs/tuples/concat.in
diff --git a/bench-run/inputs/cons.in b/bench-run/inputs/tuples/cons.in
old mode 100755
new mode 100644
similarity index 100%
rename from bench-run/inputs/cons.in
rename to bench-run/inputs/tuples/cons.in
diff --git a/bench-run/inputs/conversions.in b/bench-run/inputs/tuples/conversions.in
old mode 100755
new mode 100644
similarity index 100%
rename from bench-run/inputs/conversions.in
rename to bench-run/inputs/tuples/conversions.in
diff --git a/bench-run/inputs/map.in b/bench-run/inputs/tuples/map.in
similarity index 100%
rename from bench-run/inputs/map.in
rename to bench-run/inputs/tuples/map.in
diff --git a/bench-run/inputs/tail.in b/bench-run/inputs/tuples/tail.in
old mode 100755
new mode 100644
similarity index 100%
rename from bench-run/inputs/tail.in
rename to bench-run/inputs/tuples/tail.in
diff --git a/bench-run/inputs/zip.in b/bench-run/inputs/tuples/zip.in
similarity index 100%
rename from bench-run/inputs/zip.in
rename to bench-run/inputs/tuples/zip.in
diff --git a/bench-run/src/main/scala/Main.scala b/bench-run/src/main/scala/Main.scala
index ad102078b5b3..f0db635887d6 100644
--- a/bench-run/src/main/scala/Main.scala
+++ b/bench-run/src/main/scala/Main.scala
@@ -11,6 +11,11 @@ import scala.io.Source
 
 object Bench {
   def main(args: Array[String]): Unit = {
+    if (args.contains("--help")) {
+      printUsage()
+      return
+    }
+
     val (intArgs, args1) = args.span(x => try { x.toInt; true } catch { case _: Throwable => false } )
 
     val warmup = if (intArgs.length > 0) intArgs(0).toInt else 20
@@ -18,7 +23,8 @@ object Bench {
     val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
 
     if (args1.isEmpty) {
-      println("You should specify which benchmarks to run.")
+      println("Error: no benchmark was specified.")
+      printUsage()
       return
     }
 
@@ -36,7 +42,7 @@ object Bench {
       .resultFormat(ResultFormatType.CSV)
 
     if (args1.length > 1 && args1(1) != "--") {
-      for ((param, values) <- paramsFromFile(args1(1)))
+      for ((param, values) <- paramsFromFile("inputs/" ++ args1(1)))
         builder = builder.param(param, values: _*)
     }
 
@@ -44,8 +50,8 @@ object Bench {
       builder = builder.result(args1(2))
     }
 
-    val runner = new Runner(builder.build) // full access to all JMH features, you can also provide a custom output Format here
-    runner.run // actually run the benchmarks
+    val runner = new Runner(builder.build)
+    runner.run
   }
 
   def paramsFromFile(file: String): Array[(String, Array[String])] = {
@@ -54,4 +60,19 @@ object Bench {
       (param, values split ',')
     }
   }
+
+  def printUsage(): Unit = {
+    println()
+    println("Usage:")
+    println()
+    println("dotty-bench-run/jmh:run [<warmup>] [<iterations>] [<forks>] <regexp> [<input>|--] [<output>]")
+    println()
+    println("warmup: warmup iterations. defaults to 20.")
+    println("iterations: benchmark iterations. defaults to 20.")
+    println("forks: number of forks. defaults to 1.")
+    println("regexp: regular expression that selects which benchmarks to run.")
+    println("input: input vector file. each line should have format \'<paramName>: <comma-separated-values>\'")
+    println("output: output file for the results of benchmarks.")
+    println()
+  }
 }

From 26b98992e161a567c0312eb6701724c9c57b0f12 Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Thu, 21 Nov 2019 08:17:46 +0100
Subject: [PATCH 19/21] Revert some unwanted changes, preparing for PR

---
 bench/src/main/scala/Benchmarks.scala        | 1 +
 library/src/scala/runtime/DynamicTuple.scala | 9 +++------
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/bench/src/main/scala/Benchmarks.scala b/bench/src/main/scala/Benchmarks.scala
index 86b967762fb6..779579cd1c6b 100644
--- a/bench/src/main/scala/Benchmarks.scala
+++ b/bench/src/main/scala/Benchmarks.scala
@@ -30,6 +30,7 @@ object Bench {
     val iterations = if (intArgs.length > 1) intArgs(1).toInt else 20
     val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
 
+
     import File.{ separator => sep }
 
     val args2 = args1.map { arg =>
diff --git a/library/src/scala/runtime/DynamicTuple.scala b/library/src/scala/runtime/DynamicTuple.scala
index 53d44f75d449..ae75f133a5c1 100644
--- a/library/src/scala/runtime/DynamicTuple.scala
+++ b/library/src/scala/runtime/DynamicTuple.scala
@@ -257,12 +257,9 @@ object DynamicTuple {
     ).asInstanceOf[Zip[This, T2]]
   }
 
-  def dynamicMap[This <: Tuple, F[_]](self: This, f: [t] => t => F[t]): Map[This, F] = (self: Any) match {
-    case self: Unit => ().asInstanceOf[Map[This, F]]
-    case _ =>
-      Tuple.fromArray(self.asInstanceOf[Product].productIterator.map(f(_)).toArray) // TODO use toIArray of Object to avoid double/triple array copy
-        .asInstanceOf[Map[This, F]]
-  }
+  def dynamicMap[This <: Tuple, F[_]](self: This, f: [t] => t => F[t]): Map[This, F] =
+    Tuple.fromArray(self.asInstanceOf[Product].productIterator.map(f(_)).toArray) // TODO use toIArray of Object to avoid double/triple array copy
+      .asInstanceOf[Map[This, F]]
 
   def consIterator(head: Any, tail: Tuple): Iterator[Any] =
     Iterator.single(head) ++ tail.asInstanceOf[Product].productIterator

From 8635f1de15f9fb36496758632ffd477bbca7178b Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Thu, 21 Nov 2019 15:29:53 +0100
Subject: [PATCH 20/21] Change what was suggested in PR comments

---
 .../main/scala/{ => dotty/tools/benchmarks}/Main.scala   | 9 ++++++---
 .../{ => dotty/tools/benchmarks}/tuples/Apply.scala      | 0
 .../{ => dotty/tools/benchmarks}/tuples/ArrayOps.scala   | 0
 .../{ => dotty/tools/benchmarks}/tuples/Concat.scala     | 0
 .../scala/{ => dotty/tools/benchmarks}/tuples/Cons.scala | 0
 .../scala/{ => dotty/tools/benchmarks}/tuples/Map.scala  | 0
 .../scala/{ => dotty/tools/benchmarks}/tuples/Tail.scala | 0
 .../{ => dotty/tools/benchmarks}/tuples/TupleOps.scala   | 0
 .../scala/{ => dotty/tools/benchmarks}/tuples/Zip.scala  | 0
 9 files changed, 6 insertions(+), 3 deletions(-)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/Main.scala (91%)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/tuples/Apply.scala (100%)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/tuples/ArrayOps.scala (100%)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/tuples/Concat.scala (100%)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/tuples/Cons.scala (100%)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/tuples/Map.scala (100%)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/tuples/Tail.scala (100%)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/tuples/TupleOps.scala (100%)
 rename bench-run/src/main/scala/{ => dotty/tools/benchmarks}/tuples/Zip.scala (100%)

diff --git a/bench-run/src/main/scala/Main.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/Main.scala
similarity index 91%
rename from bench-run/src/main/scala/Main.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/Main.scala
index f0db635887d6..122dd0ce296d 100644
--- a/bench-run/src/main/scala/Main.scala
+++ b/bench-run/src/main/scala/dotty/tools/benchmarks/Main.scala
@@ -18,9 +18,12 @@ object Bench {
 
     val (intArgs, args1) = args.span(x => try { x.toInt; true } catch { case _: Throwable => false } )
 
-    val warmup = if (intArgs.length > 0) intArgs(0).toInt else 20
-    val iterations = if (intArgs.length > 1) intArgs(1).toInt else 20
-    val forks = if (intArgs.length > 2) intArgs(2).toInt else 1
+    def getIntArg(i: Int, default: Int): Int =
+      if (intArgs.length > i) intArgs(i).toInt else default
+
+    val warmup = getIntArg(0, 20)
+    val iterations = getIntArg(1, 20)
+    val forks = getIntArg(2, 1)
 
     if (args1.isEmpty) {
       println("Error: no benchmark was specified.")
diff --git a/bench-run/src/main/scala/tuples/Apply.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Apply.scala
similarity index 100%
rename from bench-run/src/main/scala/tuples/Apply.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Apply.scala
diff --git a/bench-run/src/main/scala/tuples/ArrayOps.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/tuples/ArrayOps.scala
similarity index 100%
rename from bench-run/src/main/scala/tuples/ArrayOps.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/tuples/ArrayOps.scala
diff --git a/bench-run/src/main/scala/tuples/Concat.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Concat.scala
similarity index 100%
rename from bench-run/src/main/scala/tuples/Concat.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Concat.scala
diff --git a/bench-run/src/main/scala/tuples/Cons.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Cons.scala
similarity index 100%
rename from bench-run/src/main/scala/tuples/Cons.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Cons.scala
diff --git a/bench-run/src/main/scala/tuples/Map.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Map.scala
similarity index 100%
rename from bench-run/src/main/scala/tuples/Map.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Map.scala
diff --git a/bench-run/src/main/scala/tuples/Tail.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Tail.scala
similarity index 100%
rename from bench-run/src/main/scala/tuples/Tail.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Tail.scala
diff --git a/bench-run/src/main/scala/tuples/TupleOps.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/tuples/TupleOps.scala
similarity index 100%
rename from bench-run/src/main/scala/tuples/TupleOps.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/tuples/TupleOps.scala
diff --git a/bench-run/src/main/scala/tuples/Zip.scala b/bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Zip.scala
similarity index 100%
rename from bench-run/src/main/scala/tuples/Zip.scala
rename to bench-run/src/main/scala/dotty/tools/benchmarks/tuples/Zip.scala

From e14f0b9a54b7347b4fc6430043f95645c0ac0c0f Mon Sep 17 00:00:00 2001
From: Antoine Brunner <antoine.brunner@epfl.ch>
Date: Wed, 4 Dec 2019 08:43:20 +0100
Subject: [PATCH 21/21] Fix rebase issue

---
 library/src/scala/runtime/DynamicTuple.scala | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/library/src/scala/runtime/DynamicTuple.scala b/library/src/scala/runtime/DynamicTuple.scala
index ae75f133a5c1..53d44f75d449 100644
--- a/library/src/scala/runtime/DynamicTuple.scala
+++ b/library/src/scala/runtime/DynamicTuple.scala
@@ -257,9 +257,12 @@ object DynamicTuple {
     ).asInstanceOf[Zip[This, T2]]
   }
 
-  def dynamicMap[This <: Tuple, F[_]](self: This, f: [t] => t => F[t]): Map[This, F] =
-    Tuple.fromArray(self.asInstanceOf[Product].productIterator.map(f(_)).toArray) // TODO use toIArray of Object to avoid double/triple array copy
-      .asInstanceOf[Map[This, F]]
+  def dynamicMap[This <: Tuple, F[_]](self: This, f: [t] => t => F[t]): Map[This, F] = (self: Any) match {
+    case self: Unit => ().asInstanceOf[Map[This, F]]
+    case _ =>
+      Tuple.fromArray(self.asInstanceOf[Product].productIterator.map(f(_)).toArray) // TODO use toIArray of Object to avoid double/triple array copy
+        .asInstanceOf[Map[This, F]]
+  }
 
   def consIterator(head: Any, tail: Tuple): Iterator[Any] =
     Iterator.single(head) ++ tail.asInstanceOf[Product].productIterator