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CS/CE 2336
Computer Science II
Session 11
OO Data Structures – Lists, Stacks, Queues
UT D
Adapted from D. Liang’s “Introduction to Java Programming, 8th Ed.”
2
What is a Data Structure?
• A collection of data structured (organized) in some fashion
• A data structure not only stores data, but also supports the operations for manipulating data in the structure in a certain way– E.g., an array is a data structure that holds a collection
of data in sequential order
– Array manipulation: store, retrieve, and modify data in entries of the array, find the size of the array etc…
• Array is simple and easy to use but it has limitations
3
4
Limitations of Arrays
• Once created, the size of an array cannot be altered
(cannot grow or shrink)!
• Array provides inadequate support for many
operations on its elements
– Inserting and deleting
– Sorting and searching
• Arrays are in a sense a static data structure
• But many applications require dynamic data
structures
– Data structures that can change dynamically at run-time
Object-Oriented Data Structures
• In object-oriented paradigm, a data structure is an object that stores other objects, referred to as data or elements
– Some time data structure is referred to as a container object or a collection object
– To define a data structure is essentially to declare a class
• The class for a data structure should use data fields to store elements and provide methods to support operations on its elements
– To create a data structure is therefore to create an instance from the class
– Methods of the instance are used to manipulate the data structure: inserting, deleting etc…
5
Four Classic Data Structures
• Four classic dynamic data structures to be introduced in this chapter: list, stack, queue and binary tree
• A list is a collection of data stored sequentially that supports insertion and deletion anywhere in the list
• A stack can be perceived as a special type of the list where insertions and deletions take place only at the one end, referred to as the top of a stack
• A queue represents a special list where insertions take place at the back (also referred to as the tail of) of a queue and deletions take place from the front (also referred to as the head of) of a queue
• A binary tree is a data structure to support efficient searching, sorting, inserting, and deleting data
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7
Lists
• A list is a popular data structure to store data in sequential order
• For example, a list of students, a list of available rooms, a list of cities, and a list of books, etc. can be stored using lists
• Common operations on a list
– Retrieve an element from the list
– Insert a new element to the list
– Delete an element from the list
– Find how many elements are in the list
– Determine if an element is in the list
– Determine if the list is empty (contains zero element)
Implementing a List
• Two ways to implement a list can be considered: array and linked structure
• Array– Array is used to store the elements
– The array is dynamically created
– If the capacity of the array is exceeded, create a new larger array and copy all the elements from the current array to the new array
• Linked structure– A linked structure consists of nodes
– Each node is dynamically created to hold an element
– All the nodes are linked together to form a list
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9
Design of ArrayList and LinkedList• For convenience, let’s name these two classes: MyArrayList
and MyLinkedList– These two classes have common operations, but different data fields
– The common operations can be generalized in an interface or an abstract class
• A good strategy is to combine the virtues of interfaces and abstract classes by providing both interface and abstract class in the design
– The user can use either the interface or the abstract class whichever is convenient
– Such an abstract class is known as a convenience class
M yL ist MyA bstractL ist
MyA rrayL is t
MyLi nked Lis t
MyList Interface and MyAbstractList Class
10
MyList
MyAbstractList
«interface» MyList<E>
+add(e: E) : void
+add(index: int, e: E) : void
+clear(): void
+contains(e: E): boolean
+get(index: int) : E
+indexOf(e: E) : int
+isEmpty(): boolean
+lastIndexOf(e: E) : int
+remove(e: E): boolean
+size(): int
+remove(index: int) : E
+set(index: int, e: E) : E
Appends a new element at the end of this list.
Adds a new element at the specified index in this list.
Removes all the elements from this list.
Returns true if this list contains the element.
Returns the element from this list at the specified index.
Returns the index of the first matching element in this list.
Returns true if this list contains no elements.
Returns the index of the last matching element in this list.
Removes the element from this list.
Returns the number of elements in this list.
Removes the element at the specified index and returns the removed element.
Sets the element at the specified index and returns the element you are replacing.
MyAbstractList<E>
#size: int
#MyAbstractList()
#MyAbstractList(objects: E[])
+add(e: E) : void
+isEmpty(): boolean
+size(): int
+remove(e: E): 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.
Implements the remove method.
Array Lists
• Array is a fixed-size data structure: once an array is created, its size cannot be changed but it can be used 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 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
11
Array List Animation
www.cs.armstrong.edu/liang/animation/ArrayListAnimation.html
12
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
13
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
…shift…
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
14
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
…shift…
Implementing MyArrayList
15
MyArrayList TestList
MyArrayList<E>
-data: E[]
+MyArrayList()
+MyArrayList(objects: E[])
-ensureCapacity(): void
MyAbstractList<E>
Creates a default array list.
Creates an array list from an array of objects.
Doubles the current array size if needed.
Linked Lists
• MyArrayList is implemented using an array– The methods get(int index)and set(intindex, 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
– But the methods add(int index, Object o) and remove(int index)are inefficient – Why?
– Because it requires shifting potentially a large number of elements
– A new technique is required!
• How about linked structures– A linked structure improves efficiency for adding and
removing an element anywhere in a list
16
Linked List Animation
www.cs.armstrong.edu/liang/animation/LinkedListAnimation.html
17
Nodes in Linked Lists
• A linked list consists of nodes, each node contains an element, and each node is linked to its next neighbor
• A node can be defined as a class, as follows:
18
class Node<E> {
E element;
Node next;
public Node(E o) {
element = o;
}
}
element
head
ne xt
Node 1
element
next
Node 2 …
element
null
Node n
tail
Adding Three Nodes
• The variable head refers to the first node in the list, and the variable tail 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 strings in a list, as follows:
19
Step 1: Declare head and tail:
The lis t is empty now Node<String> head = null;
Node<String> tail = null;
Adding Three Nodes - cont’d
20
Step 2: Create the first node and insert it to the list:
head "Chicago" next: null
tail
After the fi rst node is inserted inserted
head = new Node<String>("Chicago"); tail = head;
Adding Three Nodes - cont’d
21
Step 3: Create the second node and insert it to the list:
tail.next = new Node<String>("Denver");
head "Chicago" next
"Denver" next: null
tail
tail = tail.next;
head "Chicago" next
"Denver" next: null
tail
Adding Three Nodes - cont’d
22
Step 4: Create the third node and insert it to the list:
head "Chicago" next
"Dallas" next: null
tail
"Denver" next
tail.next = new Node<String>("Dallas");
head "Chicago" next
"Dallas" next: null
tail
"Denver" next
tail = tail.next;
Traversing All Elements in the List
• Each node contains the element and a data field named
next that points to the next element (the link)
• If the node is the last in the list, its data field next contains
the value null
– This property can be used to detect the last node
• List traversal
23
Node<E> current = head;
while (current != null) {
System.out.println(current.element);
current = current.next;
}
MyLinkedList
24MyLinkedList
MyLinkedList<E>
-head: Node<E>
-tail: Node<E>
+MyLinkedList()
+MyLinkedList(objects: E[])
+addFirst(e: E): void
+addLast(e: E): void
+getFirst(): E
+getLast(): E
+removeFirst(): E
+removeLast(): E
1
m Node<E>
element: E next: Node<E>
Link
1
MyAbstractList<E>
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.
Implementing addFirst(E o)
public void addFirst(E o) {Node<E> newNode = new Node<E>(o);newNode.next = head;head = newNode;size++;if (tail == null)
tail = head;}
25
head
e0
next
…
A new node to be inserted here
ei
next
ei+1
next
tail
… ek
null
element
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
tail
… ek
null
element
next
head
Implementing addLast(E o)public void addLast(E o) {
if (tail == null) {head = tail = new Node<E>(element);
}else {tail.next = new Node(element);tail = tail.next;
}size++;
}
26
head
e0
next
… ei
next
ei+1
next
tail
… ek
null
o
null
New node inserted here
(a) Before a new node is inserted.
(b) After a new node is inserted.
head
e0
next
… ei
next
ei+1
next
tail
… ek
next
A new node to be inserted here
o
null
Implementing add(int index, E o)
public void add(int index, E o) {if (index == 0) addFirst(o);else if (index >= size) addLast(o);else {Node<E> current = head;for (int i = 1; i < index; i++)current = current.next;
Node<E> temp = current.next;current.next = new Node<E>(o);(current.next).next = temp;size++;
}} 27
current head
e0
next
…
A new node to be inserted here
ei
next
temp
ei+1
next
tail
… ek
null
e
null (a) Before a new node is inserted.
current head
e0
next
…
A new node is inserted in the list
ei
next
temp
ei+1
next
tail
… ek
null
e
next (b) After a new node is inserted.
Implementing removeFirst()
public E removeFirst() {if (size == 0) return null;else {
Node<E> temp = head;head = head.next;size--;if (head == null) tail = null;return temp.element;
}} 28
head
e0
next
…
Delete this node
ei
next
ei+1
next
tail
… ek
null
(a) Before the node is deleted.
(b) After the first node is deleted
e1
next
… ei
next
ei+1
next
tail
… ek
null
e1
next
head
29
Implementing removeLast()public E removeLast() {if (size == 0) return
null;else if (size == 1){
Node<E> temp = head;head = tail = null;size = 0;return temp.element;
}else{
Node<E> current = head;for (int i = 0; i <
size - 2; i++)current =
current.next;Node temp = tail;tail = current;tail.next = null;size--;return temp.element;
}}
head
e0
next
…
Delete this node
ek-2
next
ek-1
next
tail
ek
null
(a) Before the node is deleted.
(b) After the last node is deleted
e1
next
current
head
e0
next
… ek-2
next
ek-1
null
e1
next
tail
Implementing remove(int index)
public E remove(int index){if (index < 0 || index >=
size) return null;else if (index == 0) return
removeFirst();else if (index == size - 1)
return removeLast();else {Node<E> previous = head;for (int i = 1; i < index;
i++) {previous =
previous.next;}Node<E> current =
previous.next;previous.next =
current.next;size--;return current.element;
}}
30
previous head
element
next
…
Node to be deleted
element
next
element
next
tail
… element
null
element
next
(a) Before the node is deleted.
current
previous head
element
next
… element
next
element
next
tail
… element
null
(b) After the node is deleted.
current.next
current.next
Circular Linked Lists
• A circular, singly linked list is like a singly linked
list, except that the pointer of the last node
points back to the first node
31
element
head
next
Node 1
element
next
Node 2 …
element
next
Node n
tail
Doubly Linked Lists
• A doubly linked list contains the nodes with two pointers (links)
• One points to the next node and the other points to the
previous node
• These two pointers are conveniently called a forward pointer
and a backward pointer – Why two pointers?
– A doubly linked list can be traversed both ways: forward and backward
32
element
head
next
Node 1
element
next
Node 2 …
element
null
Node n
tail
null previous previous
Circular Doubly Linked Lists
• A circular, doubly linked list is doubly linked list,
except that the forward pointer of the last node
points to the first node and the backward pointer of
the first pointer points to the last node
33
element
head
next
Node 1
element
next
Node 2 …
element
next
Node n
tail
previous previous previous
Stacks
• 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
34
Data1 Data2
Data1 Data1 Data2 Data3
Data1 Data2 Data3
Data1 Data2
Data3
Data1
Data2 Data1
Queues• 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
35
Data1 Data2
Data1 Data1 Data2 Data3
Data1 Data2 Data3
Data2 Data3
Data1
Data3
Data2 Data3
Stack Animation
www.cs.armstrong.edu/liang/animation/StackAnimation.html
36
Queue Animation
www.cs.armstrong.edu/liang/animation/QueueAnimation.html
37
Implementing Stacks and Queues
• How do we implement a Stack?
• How do we implement Queue?
• Since the insertion and deletion operations on a stack are made only at the end of the stack, using an array list to implement a stack is more efficient than a linked list
• Since deletions and insertions are made at the beginning and the end of the list, it is more efficient to implement a queue using a linked list than an array list
38
Design of the Stack and Queue Classes
Two ways to design the stack and queue classes:
– Using inheritance: declare the stack class by extending the array list class, and the queue class by extending the linked list class
39
MyArrayList MyStack MyLinkedList MyQueue
– 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
MyStack
MyArrayList MyQueue MyLinkedList
Composition is Better
• Both designs are fine, but using composition is better
• Why?
– Because composition enables the definition of a complete new stack class and queue class with only necessary attributes and methods
– No need to inherit the unnecessary and inappropriate methods from the array list and linked list
40
MyStack and MyQueue
41
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.
MyStack
MyQueue<E>
-list: MyLinkedList<E>
+enqueue(e: E): void
+dequeue(): E
+getSize(): int
Adds an element to this queue.
Removes an element from this queue.
Returns the number of elements from this queue.
MyQueue
Examples Using Stacks and Queues
Write a program that creates a stack using MyStackand a queue using MyQueue. It then uses the push(enqueue) method to add strings to the stack (or
queue) and the pop (dequeue) method to remove
strings from the stack (or queue).
42
TestStackQueue
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
– E.g., in the emergency room in a hospital assigns patients with priority numbers; the patient with the highest priority is treated first
43MyPriorityQueue TestPriorityQueue
MyPriorityQueue<E>
-heap: Heap<E>
+enqueue(element: E): void
+dequeue(): E
+getSize(): int
Adds an element to this queue.
Removes an element from this queue.
Returns the number of elements from this queue.
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