Merge pull request #293 from btakashi/master

More minor fixes to collections overview

Author: heathermiller

overviews/collections/concrete-immutable-collection-classes.md

@@ -98,7 +98,7 @@ Here are some simple operations performed on a stack:
     scala> hasOne.pop
     res19: scala.collection.immutable.Stack[Int] = Stack()
 
-Immutable stacks are used rarely in Scala programs because their functionality is subsumed by lists: A `push` on an immutable stack is the same as a `::` on a list and a `pop` on a stack is the same a `tail` on a list.
+Immutable stacks are used rarely in Scala programs because their functionality is subsumed by lists: A `push` on an immutable stack is the same as a `::` on a list and a `pop` on a stack is the same as a `tail` on a list.
 
 ## Immutable Queues
 
@@ -150,11 +150,11 @@ Ranges are represented in constant space, because they can be defined by just th
 
 Hash tries are a standard way to implement immutable sets and maps efficiently. They are supported by class [immutable.HashMap](http://www.scala-lang.org/api/{{ site.scala-version }}/scala/collection/immutable/HashMap.html). Their representation is similar to vectors in that they are also trees where every node has 32 elements or 32 subtrees. But the selection of these keys is now done based on hash code. For instance, to find a given key in a map, one first takes the hash code of the key. Then, the lowest 5 bits of the hash code are used to select the first subtree, followed by the next 5 bits and so on. The selection stops once all elements stored in a node have hash codes that differ from each other in the bits that are selected up to this level.
 
-Hash tries strike a nice balance between reasonably fast lookups and reasonably efficient functional insertions (`+`) and deletions (`-`). That's why they underly Scala's default implementations of immutable maps and sets. In fact, Scala has a further optimization for immutable sets and maps that contain less than five elements. Sets and maps with one to four elements are stored as single objects that just contain the elements (or key/value pairs in the case of a map) as fields. The empty immutable set and the empty immutable map is in each case a single object - there's no need to duplicate storage for those because and empty immutable set or map will always stay empty.
+Hash tries strike a nice balance between reasonably fast lookups and reasonably efficient functional insertions (`+`) and deletions (`-`). That's why they underly Scala's default implementations of immutable maps and sets. In fact, Scala has a further optimization for immutable sets and maps that contain less than five elements. Sets and maps with one to four elements are stored as single objects that just contain the elements (or key/value pairs in the case of a map) as fields. The empty immutable set and the empty immutable map is in each case a single object - there's no need to duplicate storage for those because an empty immutable set or map will always stay empty.
 
 ## Red-Black Trees
 
-Red-black trees are a form of balanced binary trees where some nodes are designated "red" and others designated "black." Like any balanced binary tree, operations on them reliably complete in time logarithmic to the size of the tree.
+Red-black trees are a form of balanced binary tree where some nodes are designated "red" and others designated "black." Like any balanced binary tree, operations on them reliably complete in time logarithmic to the size of the tree.
 
 Scala provides implementations of immutable sets and maps that use a red-black tree internally. Access them under the names [TreeSet](http://www.scala-lang.org/api/{{ site.scala-version }}/scala/collection/immutable/TreeSet.html) and [TreeMap](http://www.scala-lang.org/api/{{ site.scala-version }}/scala/collection/immutable/TreeMap.html).
 
@@ -164,7 +164,7 @@ Scala provides implementations of immutable sets and maps that use a red-black t
     scala> res11 + 1 + 3 + 3
     res12: scala.collection.immutable.TreeSet[Int] = TreeSet(1, 3)
 
-Red black trees are the standard implementation of `SortedSet` in Scala, because they provide an efficient iterator that returns all elements in sorted order.
+Red-black trees are the standard implementation of `SortedSet` in Scala, because they provide an efficient iterator that returns all elements in sorted order.
 
 ## Immutable BitSets
 
@@ -185,7 +185,7 @@ Operations on bit sets are very fast. Testing for inclusion takes constant time.
 
 ## List Maps
 
-A [ListMap](http://www.scala-lang.org/api/{{ site.scala-version }}/scala/collection/immutable/ListMap.html) represents a map as a linked list of key-value pairs. In general, operations on a list map might have to iterate through the entire list. Thus, operations on a list map take time linear in the size of the map. In fact there is little usage for list maps in Scala because standard immutable maps are almost always faster. The only possible difference is if the map is for some reason constructed in such a way that the first elements in the list are selected much more often than the other elements.
+A [ListMap](http://www.scala-lang.org/api/{{ site.scala-version }}/scala/collection/immutable/ListMap.html) represents a map as a linked list of key-value pairs. In general, operations on a list map might have to iterate through the entire list. Thus, operations on a list map take time linear in the size of the map. In fact there is little usage for list maps in Scala because standard immutable maps are almost always faster. The only possible exception to this is if the map is for some reason constructed in such a way that the first elements in the list are selected much more often than the other elements.
 
     scala> val map = scala.collection.immutable.ListMap(1->"one", 2->"two")
     map: scala.collection.immutable.ListMap[Int,java.lang.String] = 

overviews/collections/maps.md

@@ -74,7 +74,7 @@ Mutable maps support in addition the operations summarized in the following tabl
 |  **Cloning:**             |						     |
 |  `ms.clone`               |Returns a new mutable map with the same mappings as `ms`.|
 
-The addition and removal operations for maps mirror those for sets. As is the for sets, mutable maps also support the non-destructive addition operations `+`, `-`, and `updated`, but they are used less frequently because they involve a copying of the mutable map. Instead, a mutable map `m` is usually updated "in place", using the two variants `m(key) = value` or `m += (key -> value)`. There are is also the variant `m put (key, value)`, which returns an `Option` value that contains the value previously associated with `key`, or `None` if the `key` did not exist in the map before.
+The addition and removal operations for maps mirror those for sets. Like sets, mutable maps also support the non-destructive addition operations `+`, `-`, and `updated`, but they are used less frequently because they involve a copying of the mutable map. Instead, a mutable map `m` is usually updated "in place", using the two variants `m(key) = value` or `m += (key -> value)`. There is also the variant `m put (key, value)`, which returns an `Option` value that contains the value previously associated with `key`, or `None` if the `key` did not exist in the map before.
 
 The `getOrElseUpdate` is useful for accessing maps that act as caches. Say you have an expensive computation triggered by invoking a function `f`:
 
@@ -85,7 +85,7 @@ The `getOrElseUpdate` is useful for accessing maps that act as caches. Say you h
 
 Assume further that `f` has no side-effects, so invoking it again with the same argument will always yield the same result. In that case you could save time by storing previously computed bindings of argument and results of `f` in a map and only computing the result of `f` if a result of an argument was not found there. One could say the map is a _cache_ for the computations of the function `f`.
 
-    val cache = collection.mutable.Map[String, String]()
+    scala> val cache = collection.mutable.Map[String, String]()
     cache: scala.collection.mutable.Map[String,String] = Map()
 
 You can now create a more efficient caching version of the `f` function:
@@ -110,7 +110,7 @@ Note that the second argument to `getOrElseUpdate` is "by-name", so the computat
 
 ### Synchronized Sets and Maps ###
 
-To get a thread-safe mutable map, you can mix the `SynchronizedMap` trait trait into whatever particular map implementation you desire. For example, you can mix `SynchronizedMap` into `HashMap`, as shown in the code below. This example begins with an import of two traits, `Map` and `SynchronizedMap`, and one class, `HashMap`, from package `scala.collection.mutable`. The rest of the example is the definition of singleton object `MapMaker`, which declares one method, `makeMap`. The `makeMap` method declares its result type to be a mutable map of string keys to string values.
+To get a thread-safe mutable map, you can mix the `SynchronizedMap` trait into whatever particular map implementation you desire. For example, you can mix `SynchronizedMap` into `HashMap`, as shown in the code below. This example begins with an import of two traits, `Map` and `SynchronizedMap`, and one class, `HashMap`, from package `scala.collection.mutable`. The rest of the example is the definition of singleton object `MapMaker`, which declares one method, `makeMap`. The `makeMap` method declares its result type to be a mutable map of string keys to string values.
 
       import scala.collection.mutable.{Map,
           SynchronizedMap, HashMap}

overviews/collections/sets.md

@@ -13,12 +13,11 @@ languages: [ja]
 
 * **Tests** `contains`, `apply`, `subsetOf`. The `contains` method asks whether a set contains a given element. The `apply` method for a set is the same as `contains`, so `set(elem)` is the same as `set contains elem`. That means sets can also be used as test functions that return true for the elements they contain. 
 
-For example
+For example:
 
 
-    val fruit = Set("apple", "orange", "peach", "banana")
-    fruit: scala.collection.immutable.Set[java.lang.String] = 
-    Set(apple, orange, peach, banana)
+    scala> val fruit = Set("apple", "orange", "peach", "banana")
+    fruit: scala.collection.immutable.Set[java.lang.String] = Set(apple, orange, peach, banana)
     scala> fruit("peach")
     res0: Boolean = true
     scala> fruit("potato")
@@ -134,7 +133,7 @@ If you create new sets from a tree-set (for instance by concatenation or filteri
     scala> res2 + ("one", "two", "three", "four")
     res3: scala.collection.immutable.TreeSet[String] = TreeSet(four, one, three, two)
 
-Sorted sets also support ranges of elements. For instance, the `range` method returns all elements from a starting element up to, but excluding, and end element. Or, the `from` method returns all elements greater or equal than a starting element in the set's ordering. The result of calls to both methods is again a sorted set. Examples:
+Sorted sets also support ranges of elements. For instance, the `range` method returns all elements from a starting element up to, but excluding, an end element. Or, the `from` method returns all elements greater or equal than a starting element in the set's ordering. The result of calls to both methods is again a sorted set. Examples:
 
     scala> res3 range ("one", "two")
     res4: scala.collection.immutable.TreeSet[String] = TreeSet(one, three)