This program counts the occurrences of words in a
text and displays the words and their occurrences
in ascending order of the words. The program uses
a hash map to store a pair consisting of a word and
its count. For each word, check whether it is
already a key in the map. If not, add the key and
value 1 to the map. Otherwise, increase the value
for the word (key) by 1 in the map. To sort the
map, convert it to a tree map
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the last matching element in this list.
Removes all the elements from this list.
Returns the number of elements in this list.
Removes the element at the specified index.
Sets the element at the specified index.
MyAbstractList
#size: int
#MyAbstractList()
#MyAbstractList(objects: Object[])
+add(o: Object) : void
+add(o: Object) : void
+isEmpty(): boolean
The size of the list.
Creates a default list.
Creates a list from an array of objects.
Implements the add method.
Implements the isEmpty method.
Implements the size method.
MyList
MyAbstractList
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Array Lists
Array is a fixed-size data structure. Once an array is
created, its size cannot be changed. Nevertheless, you can
still use array to implement dynamic data structures. The
trick is to create a new larger array to replace the current
array if the current array cannot hold new elements in the
list.
Initially, an array, say data of Object[] type, is created with
a default size. When inserting a new element into the array,
first ensure there is enough room in the array. If not, create
a new array with the size as twice as the current one. Copy
the elements from the current array to the new array. The
new array now becomes the current array.
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Insertion
Before inserting a new element at a specified index,
shift all the elements after the index to the right and
increase the list size by 1.
e0
0 1 i i+1 k-1 Before inserting
e at insertion point i e1 ei ei+1
ek-1
data.length -1 Insertion point e
e0
0 1 i i+1 After inserting
e at insertion point i,
list size is
incremented by 1
e1 e ei
ek-1
data.length -1 e inserted here
ek
ek
k
ei-1
ei-1
k+1 k
ei+1
i+2
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Deletion
To remove an element at a specified index, shift all
the elements after the index to the left by one
position and decrease the list size by 1.
e0
0 1 i i+1 k-1 Before deleting the
element at index i e1 ei ei+1
ek-1
data.length -1 Delete this element
e0
0 1 i After deleting the
element, list size is
decremented by 1 e1
ek
data.length -1
ek
k
ei-1
ei-1
k-1
ei+1
k-2
ek-1
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Implementing MyArrayList
MyArrayList
-data: Object[]
+MyArrayList()
+MyArrayList(objects: Object[])
MyAbstractList
Creates a default array list.
Creates an array list from an array of objects.
MyArrayList Run TestList
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Linked Lists
Since MyArrayList is implemented using an array,
the methods get(int index) and set(int index, Object
o) for accessing and modifying an element through
an index and the add(Object o) for adding an
element at the end of the list are efficient. However,
the methods add(int index, Object o) and remove(int
index) are inefficient because it requires shifting
potentially a large number of elements. You can use
a linked structure to implement a list to improve
efficiency for adding and remove an element
anywhere in a list.
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Nodes in Linked Lists
A linked list consists of nodes, as shown in Figure 20.7.
Each node contains an element, and each node is linked
to its next neighbor. Thus a node can be defined as a
class, as follows:
first element
next
element
next
element
next
last
node1 node2 node n
class Node {
Object element;
Node next;
public Node(Object o) {
element = o;
}
}
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Nodes in a Linked List
The variable first refers to the first node in the list, and the
variable last refers to the last node in the list. If the list is empty,
both are null. For example, you can create three nodes to store
three circle objects (radius 1, 2, and 3) in a list:
Node first, last;
// Create a node to store the first circle object
first = new Node(new Circle(1));
last = first;
// Create a node to store the second circle object
last.next = new Node(new Circle(2));
last = last.next;
// Create a node to store the third circle object
last.next = new Node(new Circle(3));
last = last.next;
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MyLinkedList
MyLinkedList
-first: Node
-last: Node
+LinkedList()
+LinkedList(objects: Object[])
+addFirst(o: Object): void
+addLast(o: Object): void
+getFirst(): Object
+getLast(): Object
+removeFirst(): Object
+removeLast(): Object
1
m Node
element: Object
next: Node
Link
1
MyAbstractList
Creates a default linked list.
Creates a linked list from an array of objects.
Adds the object to the head of the list.
Adds the object to the tail of the list.
Returns the first object in the list.
Returns the last object in the list.
Removes the first object from the list.
Removes the last object from the list.
My LinkedList
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The addFirst(Object o) Method
Since variable size is defined as protected in MyAbstractList, it
can be accessed in MyLinkedList. When a new element is added
to the list, size is incremented by 1, and when an element is
removed from the list, size is decremented by 1. The
addFirst(Object o) method (Line 20-28) creates a new node to
store the element and insert the node to the beginning of the list.
After the insertion, first should refer to this new element node.
first
e0
next
A new node
to be inserted
here
ei
next
ei+1
next
last
ek
next
o
next
New node inserted here
(A) Before a new node is inserted.
(B) After a new node is inserted.
e0
next
ei
next
ei+1
next
last
ek
next
o
next
first
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The addLast(Object o) Method
The addLast(Object o) method (Lines 31-41) creates a node to
hold element o and insert the node to the end of the list. After the
insertion, last should refer to this new element node.
first
e0
next
ei
next
ei+1
next
last
ek
next
o
next
New node inserted here
(A) Before a new node is inserted.
(B) After a new node is inserted.
first
e0
next
ei
next
ei+1
next
last
ek
next
A new node
to be inserted
here
o
next
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The add(int index, Object o) Method
The add(int index, Object o) method (Lines 45-57) adds an element o
to the list at the specified index. Consider three cases: (1) if index is 0,
invoke addFirst(o) to insert the element to the beginning of the list;
(2) if index is greater than or equal to size, invoke addLast(o) to insert
the element to the end of the list; (3) create a new node to store the
new element and locate where to insert the new element. As shown in
Figure 20.12, the new node is to be inserted between the nodes
current and temp. The method assigns the new node to current.next
and assigns temp to the new node’s next.
current first
e0
next
A new node
to be inserted
here
ei
next
temp
ei+1
next
last
ek
next
o
next
current first
ei
next
New node inserted here
ei
next
temp
ei+1
next
last
ek
next
o
next
(A) Before a new node is inserted.
(B) After a new node is inserted.
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The removeFirst() Method
The removeFirst() method (Lines 61-69) removes the first node in the
list by pointing first to the second node, as shown in Figure 20.13.
The removeLast() method (Lines 73-88) removes the last node from
the list. Afterwards, last should refer to the former second-last node.
first
e0
next
Delete this node
ei
next
ei+1
next
last
ek
next
(a) Before the node is deleted.
(b) After the first node is deleted
e1
next
ei
next
ei+1
next
last
ek
next
e1
next
first
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Stacks and Queues
A stack can be viewed as a special type of list, where the
elements are accessed, inserted, and deleted only from the
end, called the top, of the stack. A queue represents a
waiting list. A queue can be viewed as a special type of list,
where the elements are inserted into the end (tail) of the
queue, and are accessed and deleted from the beginning
(head) of the queue.
Since the insertion and deletion operations on a stack are
made only the end of the stack, using an array list to
implement a stack is more efficient than a linked list. Since
deletions are made at the beginning of the list, it is more
efficient to implement a queue using a linked list than an
array list. This section implements a stack class using an
array list and a queue using a linked list.
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Design of the Stack and Queue Classes
There are two ways to design the stack and queue classes:
· Using inheritance: You can declare the stack class by
extending the array list class, and the queue class by
extending the linked list class.
· Using composition: You can declare an array list as a
data field in the stack class, and a linked list as a data field
in the queue class.
Both designs are fine, but using composition is better
because it enables you to declare a complete new stack
class and queue class without inheriting the unnecessary
and inappropriate methods from the array list and linked
list.
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MyStack and MyQueue
MyStack
-list: MyArrayList
+isEmpty(): boolean
+getSize(): int
+peek(): Object
+pop(): Object
+push(o: Object): Object
+search(o: Object): int
Returns true if this stack is empty.
Returns the number of elements in this stack.
Returns the top element in this stack.
Returns and removes the top element in this stack.
Adds a new element to the top of this stack.
Returns the position of the specified element in this stack.
MyQueue
-list: MyLinkedList
+enqueue(element: Object): void
+dequeue(): Object
+getSize(): int
Adds an element to this queue.
Removes an element from this queue.
Returns the number of elements from this queue.
MyStack
MyQueue
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Example: Using Stacks and Queues
TestStackQueue
Write a program that creates a stack using MyStack and a
queue using MyQueue. It then uses the push (enqueue)
method to add strings to the stack (queue) and the pop
(dequeue) method to remove strings from the stack
(queue).
Run
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Binary Trees
A list, stack, or queue is a linear structure that consists of a sequence
of elements. A binary tree is a hierarchical structure. It is either
empty or consists of an element, called the root, and two distinct
binary trees, called the left subtree and right subtree. Examples of
binary trees are shown in Figure 20.18.
60
55 100
57 67 107 45
G
F R
M T A
(A) (B)
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Binary Tree Terms
The root of left (right) subtree of a node is called a left
(right) child of the node. A node without children is called
a leaf. A special type of binary tree called a binary search
tree is often useful. A binary search tree (with no duplicate
elements) has the property that for every node in the tree
the value of any node in its left subtree is less than the
value of the node and the value of any node in its right
subtree is greater than the value of the node. The binary
trees in Figure 20.18 are all binary search trees. This
section is concerned with binary search trees.
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Representing Binary Trees
A binary tree can be represented using a set of linked
nodes. Each node contains a value and two links named
left and right that reference the left child and right
child, respectively, as shown in Figure 20.19.
60
55 100
57 45 67 107
root
class TreeNode {
Object element;
TreeNode left;
TreeNode right;
public TreeNode(Object o) {
element = o;
}
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Inserting an Element to a Binary Tree
If a binary tree is empty, create a root node with the new
element. Otherwise, locate the parent node for the new
element node. If the new element is less than the parent
element, the node for the new element becomes the left
child of the parent. If the new element is greater than the
parent element, the node for the new element becomes the
right child of the parent. Here is the algorithm:
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Inserting an Element to a Binary Tree
if (root == null)
root = new TreeNode(element);
else {
// Locate the parent node
current = root;
while (current != null)
if (element value < the value in current.element) {
parent = current;
current = current.left;
}
else if (element value > the value in current.element) {
parent = current;
current = current.right;
}
else
return false; // Duplicate node not inserted
// Create the new node and attach it to the parent node
if (element < parent.element)
parent.left = new TreeNode(elemenet);
else
parent.right = new TreeNode(elemenet);
return true; // Element inserted
}
For example, to insert 101 into the tree in
Figure 20.19, the parent is the node for 107.
The new node for 101 becomes the left child
of the parent. To insert 59 into the tree, the
parent is the node for 57. The new node for 59
becomes the right child of the parent, as shown
in Figure 20.20.
60
55 100
57 45 67 107
root
59 101
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Tree Traversal
Tree traversal is the process of visiting each node in the
tree exactly once. There are several ways to traverse a tree.
This section presents inorder, preorder, postorder, depth-
first, and breadth-first traversals.
The inorder traversal is to visit the left subtree of the
current node first, then the current node itself, and finally
the right subtree of the current node.
The postorder traversal is to visit the left subtree of the
current node first, then the right subtree of the current
node, and finally the current node itself.
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Tree Traversal, cont.
The breadth-first traversal is to visit the nodes level by
level. First visit the root, then all children of the root from
left to right, then grandchildren of the root from left to
right, and so on.
For example, in the tree in Figure 20.20, the inorder is 45
55 57 59 60 67 100 101 107. The postorder is 45 59 57 55
67 101 107 100 60. The preorder is 60 55 45 57 59 100 67
107 101. The breadth-first traversal is 60 55 100 45 57 67
107 59 101.
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The BinaryTree Class
Let’s define the binary tree class, named BinaryTree with
the insert, inorder traversal, postorder traversal, and
preorder traversal, as shown in Figure 20.21. Its
implementation is given as follows:
BinaryTree
-root: TreeNode
+BinaryTree()
+BinaryTree(objects: Object[])
+insert(o: Object): boolean
+inorder(): void
+preorder(): void
+postorder(): void
1
m TreeNode
element: Object
left: TreeNode
right: TreeNode
Link
1
Creates a default binary tree.
Creates a binary tree from an array of objects.
Adds an element to the binary tree.
Prints the nodes in inorder traversal.
Prints the nodes in preorder traversal.
Prints the nodes in postorder traversal.
BinaryTree
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Example: Using Binary Trees
Write a program that creates a binary tree using
BinaryTree. Add strings into the binary tree and traverse
the tree in inorder, postorder, and preorder.
BinaryTree Run
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Heap
Heap is a useful data structure for designing efficient sorting
algorithms and priority queues. A heap is a binary tree with the
following properties:
It is a complete binary tree.
Each node is greater than or equal to any of its children.
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Complete Binary Tree
A binary tree is complete if every level of the tree is full except that the last level
may not be full and all the leaves on the last level are placed left-most. For
example, in Figure 20.23, the binary trees in (a) and (b) are complete, but the
binary trees in (c) and (d) are not complete. Further, the binary tree in (a) is a heap,
but the binary tree in (b) is not a heap, because the root (39) is less than its right
child (42).
22 29 14 33
32 39
42
22 29 14
32 42
39
22 14 33
32 39
42
22 29
32
42
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Representing a Heap
For a node at position i, its left child is at position 2i+1 and its
right child is at position 2i+2, and its parent is (i-1)/2. For
example, the node for element 39 is at position 4, so its left child
(element 14) is at 9 (2*4+1), its right child (element 33) is at 10
(2*4+2), and its parent (element 42) is at 1 ((4-1)/2).
22 29 14 33 17 30 9
32 39 44 13
42 59
62
62 42 59 32 39 44 13 22 29 14 33 17 30 9
[0] [1] [2] [3] [4] [5] [6] [7] [8] [9] [10][11][12][13]
[10][11]
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Rebuilding a Heap
22 29 14 33 17 30
32 39 44 13
42 59
9
(a) After moving 9 to the root
22 29 14 33 17 30
32 39 44 13
42 9
59
(b) After swapping 9 with 59
22 29 14 33 17 30
32 39 9 13
42 44
59
(c) After swapping 9 with 44
22 29 14 33 17 9
32 39 30 13
42 44
59
(d) After swapping 9 with 30
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Removing the Root
22 29 14 33 17 30
32 39 44 13
42 59
9
(a) After moving 9 to the root
22 29 14 33 17 30
32 39 44 13
42 9
59
(b) After swapping 9 with 59
22 29 14 33 17 30
32 39 9 13
42 44
59
(c) After swapping 9 with 44
22 29 14 33 17 9
32 39 30 13
42 44
59
(d) After swapping 9 with 30
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Adding a New Node
22 29 14 33 17 88
32 39 30 13
42 44
59
(a) Add 88 into an existing heap
22 29 14 33 17 30
32 39 88 13
42 44
59
(b) After swapping 88 with 30
22 29 14 33 17 30
32 39 44 13
42 88
59
(c) After swapping 88 with 44
22 29 14 33 17 30
32 39 44 13
42 59
88
(d) After swapping 88 with 59
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The Heap Class
Heap
-list: java.util.ArrayList
+Heap()
+Heap(objects: Object[])
+remove(): Object
+add(newObject: Object): void
+getSize(): int
Creates a default heap.
Creates a heap with the specified objects.
Removes the root from the heap and returns it.
Adds a new object to the heap.
Returns the size of the heap.
Heap Run TestHeap
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Priority Queue
A regular queue is a first-in and first-out data structure. Elements are
appended to the end of the queue and are removed from the
beginning of the queue. In a priority queue, elements are assigned
with priorities. When accessing elements, the element with the
highest priority is removed first. A priority queue has a largest-in,
first-out behavior. For example, the emergency room in a hospital
assigns patients with priority numbers; the patient with the highest
priority is treated first.
MyPriorityQueue
-heap: Heap
+enqueue(element: Object): void
+dequeue(): Object
+getSize(): int
Adds an element to this queue.
Removes an element from this queue.
Returns the number of elements from this queue.
MyPriorityQueue Run TestPriorityQueue
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Java Collection Framework
hierarchy
A collection is a container object that
represents a group of objects, often
referred to as elements. The Java
Collections Framework supports three
types of collections, named sets, lists, and
maps.
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Java Collection Framework
hierarchy, cont.
Set and List are subinterfaces of Collection.
Set
SortedSet
AbstractSet
Collection
TreeSet
HashSet
List AbstractList
AbstractSequentialList
ArrayList
LinkedList
AbstractCollection
Vector Stack
LinkedHashSet
Interfaces Abstract Classes Concrete Classes
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Java Collection Framework
hierarchy, cont.
An instance of Map represents a group of objects, each
of which is associated with a key. You can get the
object from a map using a key, and you have to use a
key to put the object into the map.
SortedMap
Map
TreeMap
HashMap AbstractMap LinkedHashMap
Interfaces Abstract Classes Concrete Classes
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The Collection Interface
«interface»
java.util.Collection
+add(o: E): boolean
+addAll(c: Collection<? extends E): boolean
+clear(): void
+contains(o: Object): boolean
+containsAll(c: Collection):boolean
+equals(o: Object): boolean
+hashCode(): int
+isEmpty(): boolean
+iterator(): Iterator
+remove(o: Object): boolean
+removeAll(c: Collection): boolean
+retainAll(c: Collection): boolean
+size(): int
+toArray(): Object[]
Adds a new element o to this collection.
Adds all the elements in the collection c to this collection.
Removes all the elements from this collection.
Returns true if this collection contains the element o.
Returns true if this collection contains all the elements in c.
Returns true if this collection is equal to another collection o.
Returns the hash code for this collection.
Returns true if this collection contains no elements.
Returns an iterator for the elements in this collection.
Removes the element o from this collection.
Removes all the elements in c from this collection.
Retains the elements that are both in c and in this collection.
Returns the number of elements in this collection.
Returns an array of Object for the elements in this collection.
«interface»
java.util.Iterator
+hasNext(): boolean
+next(): E
+remove(): void
Returns true if this iterator has more elements to traverse.
Returns the next element from this iterator.
Removes the last element obtained using the next method.
The Collection interface is the root interface
for manipulating a collection of objects.
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The Set Interface
The Set interface extends the Collection
interface. It does not introduce new methods or
constants, but it stipulates that an instance of
Set contains no duplicate elements. The concrete
classes that implement Set must ensure that no
duplicate elements can be added to the set. That
is no two elements e1 and e2 can be in the set
such that e1.equals(e2) is true.
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The Set Interface Hierarchy
java.util.AbstractSet
java.util.HashSet
+HashSet()
+HashSet(c: Collection)
java.util.LinkedHashSet
+LinkedHashSet()
+LinkedHashSet(c: Collection<?
extends E>)
java.util.TreeSet
+TreeSet()
+TreeSet(c: Collection)
+TreeSet(c: Comparator)
«interface»
java.util.SortedSet
+first(): E
+last(): E
+headSet(toElement: E): SortedSet
+tailSet(fromElement: E): SortedSet
«interface»
java.util.Set
Returns the first in this set.
Returns the last in this set.
headSet/tailSet returns a
portion of the set less
than toElement/greater
than fromElement.
Creates a tree set with the
specified comparator.
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The AbstractSet Class
The AbstractSet class is a convenience class that
extends AbstractCollection and implements Set.
The AbstractSet class provides concrete
implementations for the equals method and the
hashCode method. The hash code of a set is the
sum of the hash code of all the elements in the
set. Since the size method and iterator method
are not implemented in the AbstractSet class,
AbstractSet is an abstract class.
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The HashSet Class
The HashSet class is a concrete class that
implements Set. It can be used to store
duplicate-free elements. For efficiency,
objects added to a hash set need to
implement the hashCode method in a
manner that properly disperses the hash
code.
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Example: Using HashSet and
Iterator
This example creates a hash set filled
with strings, and uses an iterator to
traverse the elements in the list.
TestHashSet Run
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TIP
You can simplify the code in Lines 21-26 using
a JDK 1.5 enhanced for loop without using an
iterator, as follows:
for (Object element: set)
System.out.print(element.toString() + " ");
JDK 1.5
Feature
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Example: Using LinkedHashSet
This example creates a hash set filled
with strings, and uses an iterator to
traverse the elements in the list.
TestLinkedHashSet Run
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The SortedSet Interface and the
TreeSet Class
SortedSet is a subinterface of Set, which
guarantees that the elements in the set are
sorted. TreeSet is a concrete class that
implements the SortedSet interface. You
can use an iterator to traverse the
elements in the sorted order. The elements
can be sorted in two ways.
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The SortedSet Interface and the
TreeSet Class, cont.
One way is to use the Comparable interface.
The other way is to specify a comparator for
the elements in the set if the class for the
elements does not implement the Comparable
interface, or you don’t want to use the
compareTo method in the class that
implements the Comparable interface. This
approach is referred to as order by comparator.
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Example: Using TreeSet to Sort
Elements in a Set
This example creates a hash set filled with strings,
and then creates a tree set for the same strings. The
strings are sorted in the tree set using the
compareTo method in the Comparable interface.
The example also creates a tree set of geometric
objects. The geometric objects are sorted using the
compare method in the Comparator interface.
GeometricObjectComparator Run
TestTreeSet
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The Comparator Interface
Sometimes you want to insert elements of different
types into a tree set. The elements may not be
instances of Comparable or are not comparable. You
can define a comparator to compare these elements.
To do so, create a class that implements the
java.util.Comparator interface. The Comparator
interface has two methods, compare and equals.
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The Comparator Interface
public int compare(Object element1, Object
element2)
Returns a negative value if element1 is less than
element2, a positive value if element1 is greater than
element2, and zero if they are equal.
public boolean equals(Object element)
Returns true if the specified object is also a
comparator and imposes the same ordering as this
comparator.
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Example: The Using Comparator to
Sort Elements in a Set
Write a program that demonstrates how
to sort elements in a tree set using the
Comparator interface. The example
creates a tree set of geometric objects.
The geometric objects are sorted using
the compare method in the Comparator
interface.
TestTreeSetWithComparator Run
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The List Interface
A set stores non-duplicate elements. To
allow duplicate elements to be stored in a
collection, you need to use a list. A list
can not only store duplicate elements,
but can also allow the user to specify
where the element is stored. The user
can access the element by index.
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The List Interface, cont.
List
+add(index: int, element: Object) : boolean
+addAll(index: int, collection: Collection) :
boolean
+get(index: int) : Object
+indexOf(element: Object) : int
+lastIndexOf(element: Object) : int
+listIterator() : ListIterator
+listIterator(startIndex: int) : ListIterator
+remove(index: int) : int
+set(index: int, element: Object) : Object
+subList(fromIndex: int, toIndex: int) : List
Collection
Adds a new element at the specified index
Adds all elements in the collection to this list at the
specified index
Returns the element in this list at the specified index
Returns the index of the first matching element
Returns the index of the last matching element
Returns the list iterator for the elements in this list
Returns the iterator for the elements from startIndex
Removes the element at the specified index
Sets the element at the specified index
Returns a sublist from fromIndex to toIndex
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The List Iterator
ListIterator
+add(o: Object) : void
+hasPrevious() : boolean
+nextIndex() : int
+previousIndex() : int
+previous() : Object
+set(o: Object) : void
Iterator
Adds the specified object to the list
Returns true if this list iterator has more elements
when traversing backward.
Returns the index of the next element
Returns the index of the previosu element
Returns the previous element in this list iterator
Replaces the last element returned by the previous
or next method with the specified element
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ArrayList and LinkedList
The ArrayList class and the LinkedList class are
concrete implementations of the List interface. Which
of the two classes you use depends on your specific
needs. If you need to support random access through
an index without inserting or removing elements from
any place other than the end, ArrayList offers the
most efficient collection. If, however, your application
requires the insertion or deletion of elements from any
place in the list, you should choose LinkedList. A list
can grow or shrink dynamically. An array is fixed
once it is created. If your application does not require
insertion or deletion of elements, the most efficient
data structure is the array.
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LinkedList
LinkedList
+addFirst(o: Object) : void
+addLast(o: Object) : void
+getFirst() : Object
+getLast() : Object
+removeFirst() : Object
+removeLast() : Object
List
AbstractSequentialList
Adds the object to the head of this list
Adds the object to the tail of this list
Returns the first element from this list
Returns the last element from this list
Returns and removes the first element from this list
Returns and removes the last element from this list
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Example: Using ArrayList and
LinkedList
This example creates an array list filled
with numbers, and inserts new elements
into the specified location in the list. The
example also creates a linked list from
the array list, inserts and removes the
elements from the list. Finally, the
example traverses the list forward and
backward.
Run TestList
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The Vector and Stack Classes
The Java Collections Framework was
introduced with Java 2. Several data
structures were supported prior to Java 2.
Among them are the Vector class and the
Stack class. These classes were redesigned to
fit into the Java Collections Framework, but
their old-style methods are retained for
compatibility. This section introduces the
Vector class and the Stack class.
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The Vector Class
In Java 2, Vector is the same as ArrayList,
except that Vector contains the synchronized
methods for accessing and modifying the
vector. None of the new collection data
structures introduced so far are synchronized.
If synchronization is required, you can use the
synchronized versions of the collection classes.
These classes are introduced later in the
section, “The Collections Class.”
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The Vector Class, cont.
Vector
+addElement(o: Object): void
+capacity(): int
+copyInto(anArray: Object[]): void
+elementAt(index: int): Object
+elements(): Enumeration
+ensureCapacity(): void
+firstElement(): Object
+insertElementAt(o: Object, index: int): void
+lastElement(): Object
+removeAllElements() : void
+removeElement(o: Object) : boolean
+removeElementAt(index: int) : void
+setElementAt(o: Object, index: int) : void
+setSize(newSize: int) : void
+trimToSize() : void
List
Appends the element to the end of this vector
Returns the current capacity of this vector
Copies the elements in this vector to the array
Returns the object at the specified index
Returns an emulation of this vector
Increases the capacity of this vector
Returns the first element in this vector
Inserts o to this vector at the specified index
Returns the last element in this vector
Removes all the elements in this vector
Removes the first matching element in this vector
Removes the element at the specified index
Sets a new element at the specified index
Sets a new size in this vector
Trims the capacity of this vector to its size
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The Stack Class
The Stack class represents a last-in-
first-out stack of objects. The elements
are accessed only from the top of the
stack. You can retrieve, insert, or
remove an element from the top of the
stack.
Stack
+empty(): boolean
+peek(): Object
+pop(): Object
+push(o: Object) : Object
+search(o: Object) : int
Vector
Returns true if this stack is empty
Returns the top element in this stack
Returns and removes the top element in this stack
Adds a new element to the top of this stack
Returns the position of the specified element in this stack
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Example: Using the Vector
Class
Listing 4.1, PrimeNumber.java, determines whether a
number n is prime by checking whether 2, 3, 4, 5, 6, ...,
n/2 is a divisor. If a divisor is found, n is not prime. A
more efficient approach to determine whether n is
prime is to check if any of the prime numbers less than
or equal to can divide n evenly. If not, n is prime.
Write a program that finds all the prime numbers less
than 250.
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Example: Using the Vector
Class, cont.
The program stores the prime numbers in a
vector. Initially, the vector is empty. For n = 2,
3, 4, 5, ..., 250, the program determines whether
n is prime by checking if any prime number less
than or equal to in the vector is a divisor for n.
If not, n is prime and add n to the vector. The
program that uses a vector is given below.
Run FindPrimeUsingVector
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Example: Using the Stack Class
Write a program that reads a positive integer
and displays all its distinct prime factors in
decreasing order. For example, if the input
integer is 6, its distinct prime factors displayed
are 3, 2; if the input integer is 12, the distinct
prime factors are also 3 and 2.
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Example: Using the Stack Class,
cont.
The program uses a stack to store all the distinct
prime factors. Initially, the stack is empty. To
find all the distinct prime factors for an integer
n, use the following algorithm:
Run FindPrimeFactorUsingStack
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The Map Interface
The Map interface maps keys to the elements.
The keys are like indexes. In List, the indexes
are integer. In Map, the keys can be any
objects.
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The Map Interface UML
Diagram Map
+clear(): void
+containsKey(key: Object): boolean
+containsValue(value: Object): boolean
+entrySet(): Set
+get(key: Object): Object
+isEmpty(): boolean
+keySet(): Set
+put(key: Object, value: Object): Object
+putAll(m: Map): void
+remove(key: Object): Object
+size(): int
+values(): Collection
Removes all mappings from this map
Returns true if this map contains a mapping for the
specified key.
Returns true if this map maps one or more keys to
the specified value.
Returns a set consisting of the entries in this map
Returns the value for the specified key in this map
Returns true if this map contains no mappings
Returns a set consisting of the keys in this map
Puts a mapping in this map
Adds all mappings from m to this map
Removes the mapping for the specified key
Returns the number of mappings in this map
Returns a collection consisting of values in this map
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HashMap and TreeMap
The HashMap and TreeMap classes are
two concrete implementations of the Map
interface. The HashMap class is efficient
for locating a value, inserting a mapping,
and deleting a mapping. The TreeMap
class, implementing SortedMap, is efficient
for traversing the keys in a sorted order.
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LinkedHashMap
LinkedHashMap was introduced in JDK 1.4. It extends
HashMap with a linked list implementation that
supports an ordering of the entries in the map. The
entries in a HashMap are not ordered, but the entries in
a LinkedHashMap can be retrieved in the order in
which they were inserted into the map (known as the
insertion order), or the order in which they were last
accessed, from least recently accessed to most recently
(access order). The no-arg constructor constructs a
LinkedHashMap with the insertion order. To construct
a LinkedHashMap with the access order, use the
LinkedHashMap(initialCapacity, loadFactor, true).
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Example: Using HashMap and
TreeMap
This example creates a hash map that
maps borrowers to mortgages. The
program first creates a hash map with the
borrower’s name as its key and mortgage
as its value. The program then creates a
tree map from the hash map, and
displays the mappings in ascending order
of the keys. Run TestMap
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Example: Counting the
Occurrences of Words in a Text
This program counts the occurrences of words in a
text and displays the words and their occurrences
in ascending order of the words. The program uses
a hash map to store a pair consisting of a word and
its count. For each word, check whether it is
already a key in the map. If not, add the key and
value 1 to the map. Otherwise, increase the value
for the word (key) by 1 in the map. To sort the
map, convert it to a tree map.
Run CountOccurrenceOfWords
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The Collections Class
The Collections class contains various static methods for
operating on collections and maps, for creating
synchronized collection classes, and for creating read-
only collection classes.
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The Collections Class UML
Diagram
java.util.Collections
+sort(list: List): void
+sort(list: List, c: Comparator): void
+binarySearch(list: List, key: Object): int
+binarySearch(list: List, key: Object, c:
Comparator): int
+reverse(list: List): void
+reverseOrder(): Comparator
+shuffle(list: List): void
+shuffle(list: List): void
+copy(des: List, src: List): void
+nCopies(n: int, o: Object): List
+fill(list: List, o: Object): void
+max(c: Collection): Object
+max(c: Collection, c: Comparator): Object
+min(c: Collection): Object
+min(c: Collection, c: Comparator): Object
+disjoint(c1: Collection, c2: Collection):
boolean
+frequency(c: Collection, o: Object): int
Sorts the specified list.
Sorts the specified list with the comparator.
Searches the key in the sorted list using binary search.
Searches the key in the sorted list using binary search
with the comparator.
Reverses the specified list.
Returns a comparator with the reverse ordering.
Shuffles the specified list randomly.
Shuffles the specified list with a random object.
Copies from the source list to the destination list.
Returns a list consisting of n copies of the object.
Fills the list with the object.
Returns the max object in the collection.
Returns the max object using the comparator.
Returns the min object in the collection.
Returns the min object using the comparator.
Returns true if c1 and c2 have no elements in common.
Returns the number of occurrences of the specified
element in the collection.
List
Collection
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Example: Using the Collections
Class
This example demonstrates using the
methods in the Collections class. The
example creates a list, sorts it, and searches
for an element. The example wraps the list
into a synchronized and read-only list.
Run TestCollections
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The Arrays Class
The Arrays class contains various static methods for
sorting and searching arrays, for comparing arrays, and
for filling array elements. It also contains a method for
converting an array to a list.
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The Arrays Class UML Diagram
Arrays
+asList(a: Object[]): List
Overloaded binarySearch method for byte, char,
short, int, long, float, double, and Object.
+binarySearch(a: xType[], key: xType): int
Overloaded equals method for boolean, byte,
char, short, int, long, float, double, and Object.
+equals(a: xType[], a2: xType[]): boolean
Overloaded fill method for boolean char, byte,
short, int, long, float, double, and Object.
+fill(a: xType[], val: xType): void
+fill(a: xType[], fromIndex: int, toIndex: xType,
val: xType): void
Overloaded sort method for char, byte, short, int,
long, float, double, and Object.
+sort(a: xType[]): void
+sort(a: xType[], fromIndex: int, toIndex: int):
void
Returns a list from an array of objects
Overloaded binary search method to search a key
in the array of byte, char, short, int, long, float,
double, and Object
Overloaded equals method that returns true if a is
equal to a2 for a and a2 of the boolean, byte, char,
short, int, long, float, and Object type
Overloaded fill method to fill in the specified
value into the array of the boolean, byte, char,
short, int, long, float, and Object type
Overloaded sort method to sort the specified array
of the char, byte, short, int, long, float, double,
and Object type
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Example: Using the Arrays
Class
This example demonstrates using the
methods in the Arrays class. The example
creates an array of int values, fills part of
the array with 50, sorts it, searches for an
element, and compares the array with
another array.
Run TestArrays
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