Unit 5 dsa QUEUE

Feb 12, 20200 likes90 views

PUNE VIDYARTHI GRIHA'S COLLEGE OF ENGINEERING, NASHIK

The document discusses different implementations of queues using arrays and linked lists, as well as circular queues which avoid issues with arrays filling up by connecting the last element to the first. It covers common queue operations and describes how queues are widely used in applications like operating systems, databases, and simulations for tasks like job scheduling where elements need to be processed in a first-in, first-out order. Circular queues are presented as an efficient approach to implement queues using arrays without capacity issues.

Introduction of Queue
➢ “A queue is an ordered list in which all insertions are
done at one end, called rear and deletions at another end
called front“
➢ Queue when implemented using arrays has some
drawbacks which can be avoided by circular queue
➢ Queue is used in many applications such as as simulation,
priority queue, job queueetc

Introduction of Queue
➢ One of the most common dataprocessing structures
➢ Frequently used in most of the system software's like
operating systems, Network and Database
implementations and in many more other areas
➢ Very useful in time-sharing and distributed computer
systems where many widely distributed users share the
system simultaneously

Array representation and
implementation of queue
➢ An array representation of queue require three entities :
1. An array to hold queue element
2. A variable to hold index of the front element
3. A variable to hold index of the rear element

Array representation and
implementation of queue

Operation on queue
implemented using array

Queue as an ADT
➢ Create : Create creates an empty queue, Q
➢ Add (i,Q) : Add adds the element i to the rear end of queue,
Q and returns the newqueue
➢ Delete (Q) : Delete takes out an element i from the
➢ front end of queue and returns the resulting queue
➢ Front(Q) : Front returns the element i which is at the front
position of queue
➢ Is_Empty_Q(Q) : Is_Empty_Q returns true if queue is
➢ empty otherwise returns false

Operation on queue implemented using
Linked list

6-29
Second Approach: Queue as a
Circular Array
• If we don't fix one end of the queue at
index 0, we won't have to shift elements
• Circular array is an array that conceptually
loops around on itself
o The last index is thought to “precede” index 0
o In an array whose last index is n, the location “before” index 0 is index n;
the location “after” index n is index 0
• Need to keep track of where the front as
well as the rear of the queue are at any
given time

6-30
Conceptual Example of a Circular Queue
1
0
12
11
10
1
0
12
11
10
1
0
12
11
10
After 7 enqueues
front
rear
After 5
dequeues
front
rear
After 8 more enqueues
front
rear

6-31
Implementation of a
Queue
rear
front
5
queue
count
8
3
0
1
2 3 4
5
6
7
8
9
10
n-1
n-2
n-3
. ..
cq

6-32
A Queue Straddling the
End of a Circular Array
rear
front
4
queue
count
2
98
0
1
2 3 4
5
6
7
8
9
10
99
98
97
. ..
cq

6-33
Circular Queue Drawn
Linearly
rear
front
4
queue
count
2
98
0 4321 96 97 98 99
…
Queue from previous slide
cq

6-34
Circular Array
Implementation
• When an element is enqueued, the value of rear is
incremented
• But it must take into account the need to loop back
to index 0:
rear = (rear+1) % queue.length;
• Can this array implementation also reach capacity?

6-35
Example: array of length 4
What happens?
rear
front
3
queue
count
1
2
0 321
rear
front
4
queue
count
2
2
0 321
Suppose we try to add one
more item to a queue
implemented by an array of
length 4
cq
cq
The queue is now full. How
can you tell?

6-36
Need to expand
capacity…
rear
front
4
queue
count
2
2
0 321
rear
front
4
queue
count
2
2
0 321 4 765
We can’t just double the
size of the array and
copy values to the same
positions as before:
circular properties of the
queue will be lost
These locations
should be in use
cq
cq

6-37
rear
front
4
queue
count
6
2
0 321 4 765
We could build the new array, and copy the queue elements into
contiguous locations beginning at location front:
cq

6-38
rear
front
4
queue
count
4
0
0 321 4 765
Better: copy the queue elements in order to the beginning of the
new array
cq

6-39
rear
front
5
queue
count
5
0
0 321 4 765
New element is added at rear = (rear+1) % queue.length
See expandCapacity() in CircularArrayQueue.java
cq

Implementation of DeQueue using linked list

C function for deque using circular array

A circular queue is a fixed size data structure that follows FIFO (first in, first out) principles. Elements are added to the rear of the queue and removed from the front. When the rear reaches the end, it wraps around to the beginning so the queue space is used efficiently. Common circular queue operations include enqueue to add an element, dequeue to remove an element, and display to output all elements.

basics of queuessirmanohar

The document describes how queues work and two methods for implementing queues - using an array or linked list. It explains that queues follow a first-in first-out (FIFO) ordering, with new elements added to the rear and elements removed from the front. The key queue operations of enqueue (add to rear) and dequeue (remove from front) are also defined. Implementation using an array requires tracking the number of elements, front index, and rear index, while a linked list uses head and tail pointers.

DsSubha Selvam

This document discusses queues as an abstract data type (ADT) in data structures. It defines queues as first-in, first-out (FIFO) lists where elements are inserted at one end and removed from the other. The primary operations for queues are enqueue, which adds an element to the end, and dequeue, which removes an element from the front. Circular queues are also described, which connect the last queue position back to the first to form a circle. Common applications of queues include printer jobs, customer calls, and file server access control.

Queues presentationToseef Hasan

The document discusses different types of queues including simple queue, circular queue, priority queue, and deque. A simple queue follows FIFO principle but has limitations as items can only be inserted once. A circular queue overcomes this by allowing the rear and front pointers to wrap around. A priority queue inserts or deletes items based on priority. Deque allows insertions and deletions on both ends.

Insertion sort Monalisa Patel

This document discusses insertion sort, including its mechanism, algorithm, runtime analysis, advantages, and disadvantages. Insertion sort works by iterating through an unsorted array and inserting each element into its sorted position by shifting other elements over. Its worst case runtime is O(n^2) when the array is reverse sorted, but it performs well on small, nearly sorted lists. While simple to implement, insertion sort is inefficient for large datasets compared to other algorithms.

Insertion sortAbdelrahman Saleh

The document describes insertion sort, including an example with figures, the algorithm, implementations in Java, C++ and Python, runtime performance of Θ(n2) in the average and worst cases but Θ(n) in the best case, an example execution on sample input data, and some other notes about its properties. It is a simple sorting algorithm that works by building up a sorted sequence from left to right by inserting each element into its sorted position.

Implementation of queue using singly and doubly linked list.central university of bihar

Insertion sortalmaqboli

Insertion sort works by iterating through an array, inserting each element into its sorted position by shifting other elements over. It finds the location where each element should be inserted into the sorted portion using a linear search, moving larger elements out of the way to make room. This sorting algorithm is most effective for small data sets and can be implemented recursively or iteratively through comparisons and shifts.

Complexity of algorithmsJasur Ahmadov

Deletion operation in array(ds)chauhankapil

Deletion operation in an array involves shifting elements to the left to fill the space left by the deleted element. The algorithm shifts each element from index i+1 to the left by one index to overwrite the deleted element at index i. It then decrements the last index of the array by one to account for the reduced length. For example, to delete element E from the array, element F would shift to index 3, G to index 4, and so on, and the last index would decrement from 8 to 7.

Array stack-queue1Rajendran

This document discusses data structures and abstract data types (ADTs). It defines a data structure as a way to store and organize data, and an ADT as a collection of data with a set of operations that specify what the operations do but not how they are implemented. Common operations on data include adding, removing, and querying elements. ADTs help manage complexity by hiding implementation details. Specific data structures like stacks and queues are then discussed as examples. Stacks follow last-in, first-out (LIFO) behavior using push and pop operations, while queues follow first-in, first-out (FIFO) behavior using enqueue and dequeue. Both can be implemented using arrays or linked lists.

Ch06 Stackleminhvuong

The document discusses stacks, including defining a stack as a linear collection where elements are added and removed from one end with LIFO behavior. It examines stack implementations using arrays and linked nodes, and demonstrates how stacks can be used to solve problems like evaluating postfix expressions and maze traversal by trying alternatives in a depth-first manner using recursion simulation.

IRJET- Comparison of Stack and Queue Data StructuresIRJET Journal

This document compares the data structures of stacks and queues. Stacks follow the LIFO (last-in, first-out) principle where elements are inserted and removed from one end, while queues follow the FIFO (first-in, first-out) principle where elements are inserted at the rear and removed from the front. Both can be implemented using arrays. The main operations for stacks are push to insert and pop to remove, while for queues they are insertion to add to the rear and deletion to remove from the front. Stacks have faster insertion and removal times of O(1) compared to queues which have O(1) insertion but O(n) removal in the worst case. Both structures are commonly used in

Quick sortAbdelrahman Saleh

Quicksort is a divide and conquer algorithm that works by picking an element as a pivot and partitioning the array around it. It recursively sorts elements before and after the pivot. The average runtime is O(n log n) but it can be O(n^2) in the worst case if the pivot selection is poor. The algorithm involves picking a pivot element, partitioning the array around it, and then recursively sorting the subarrays.

Functions 2 inverse , compositeestelav

1. The document discusses composition of functions and inverse functions. It provides examples of composing functions, finding inverse functions, and sketching the graphs of functions and their inverses. 2. Key concepts covered include the domain and range requirements for functions to be composable, identifying which functions have inverses, finding inverse functions both algebraically and graphically, and properties of inverse functions like being reflections over the line y=x. 3. Examples involve composing functions like f(g(x)), finding the inverses of functions like y=3x+2, and sketching the graphs of functions and their inverses.

Linear searchAbdelrahman Saleh

This document summarizes the linear search algorithm. It begins with an introduction describing the problem of searching for an element x in an array. It then provides an example with figures and outlines the algorithm which is to start from the leftmost element and compare each element to x. Implementation in various languages is shown. Runtime is analyzed as theta(n) in best, average and worst cases. An example execution is provided to search for the element 2 in a sample array. Other notes classify it as a linear approach and stable algorithm but note it is rarely used practically due to faster alternatives like binary search.

Quick sortamar kakde

Quicksort is a divide and conquer algorithm that works by partitioning an array around a pivot value and recursively sorting the sub-partitions. It first chooses a pivot element and partitions the array by placing all elements less than the pivot before it and all elements greater than it after it. It then recursively quicksorts the two partitions. This continues until the individual partitions only contain single elements at which point they are sorted. Quicksort has average case performance of O(n log n) time making it very efficient for large data sets.

Quick and radix sortAaron Joaquin

Quicksort is a sorting algorithm developed by Tony Hoare in 1960 that uses a divide-and-conquer approach. It works by first selecting a pivot element and partitioning the array around it, such that all elements with values less than the pivot come before elements with values greater than the pivot. It then recursively applies the same approach to the sub-arrays until the entire list is sorted. Radix sort is a non-comparative integer sorting algorithm that sorts data by grouping keys based on their individual digit values at each significant position. It makes multiple passes over the data, sorting by one digit on each pass in order of significant value.

4 chapter3 list_stackqueuepart1SSE_AndyLi

The document discusses three basic data structures - lists, stacks, and queues. It describes lists and their operations like printing, finding elements, inserting, and removing elements. Lists can be implemented using arrays or linked lists. Linked lists allow constant-time insertion and removal by linking nodes through next pointers. The document also provides code for initializing, inserting, and removing elements from a doubly linked list.

Java 8 Concurrency UpdatesDamian Łukasik

Linear timesortingInternational Islamic University

The document discusses counting sort, a linear time sorting algorithm. Counting sort runs in O(n) time when the integers being sorted are in the range of 1 to k, where k is O(n). It works by counting the number of elements less than or equal to each unique input element, and using this to directly place each element in the correct position of the output array. Pseudocode and an example are provided to demonstrate how counting sort iterates through the input, counts the occurrences of each unique element, and uses this to sort the elements into the output array in linear time. However, counting sort has limitations and may not be practical for large datasets due to its required extra storage space.

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Row Reducingnicholsm

Row reducing allows you to systematically manipulate a matrix into reduced row echelon form using elementary row operations. These operations include swapping two rows, multiplying a row by a non-zero constant, and adding a multiple of one row to another. The document provides an example of using row operations like choosing pivots to get zeros below and above the pivot entries. It also shows expressing the solution of a system of equations in terms of parameters when there are more unknowns than equations.

Quick Sort , Merge Sort , Heap SortMohammed Hussein

The document discusses various sorting algorithms that use the divide-and-conquer approach, including quicksort, mergesort, and heapsort. It provides examples of how each algorithm works by recursively dividing problems into subproblems until a base case is reached. Code implementations and pseudocode are presented for key steps like partitioning arrays in quicksort, merging sorted subarrays in mergesort, and adding and removing elements from a heap data structure in heapsort. The algorithms are compared in terms of their time and space complexity and best uses.

Lecture 10 ME 176 Reduction Of Multiple SuLeonides De Ocampo

This document discusses signal flow graphs and Mason's Rule for analyzing control systems. Signal flow graphs represent systems as nodes connected by branches, with transfer functions on the branches. Mason's Rule is used to evaluate closed-loop transfer functions. It involves identifying open-loop gains along forward paths and closed-loop gains for individual loops and combinations of non-touching loops. An example applies Mason's Rule by finding relevant gains and evaluating the closed-loop transfer function according to the rule. Laboratory materials for applying these concepts can be accessed online.

Comparing two electric motors tmidTeresa Middleton

Stacksamitphadikar2012

This document discusses stacks as a linear data structure. Stacks follow the LIFO (last-in, first-out) principle, where elements can only be added or removed from one end called the top. Stacks have operations like push, pop and peek. Push adds an element to the top, pop removes from the top, and peek returns the top element without removing it. Stacks can be implemented using arrays or linked lists. The document provides algorithms for push, pop and peek operations on both array-based and linked stacks. It also lists some applications of stacks like reversing lists, parentheses checking, expression conversions, recursion and Tower of Hanoi problem.

Unit 4 queueDabbal Singh Mahara

The document discusses different types of queues and their implementations. It begins by defining a queue as a first-in first-out (FIFO) data structure where elements are inserted at the rear and deleted from the front. It then covers linear and circular queue implementations using arrays, including operations like insertion, deletion, checking for empty/full, and traversal. Priority queues are also introduced, which process elements based on assigned priorities. The key types and operations of queues as an abstract data type (ADT) are summarized.

stacks and queues for publiciqbalphy1

This document discusses stacks and queues as data structures. It begins by defining a stack as a linear collection where elements are added and removed from the top in a last-in, first-out (LIFO) manner. Common stack operations like push, pop, and peek are described. It then discusses applications of stacks like undo sequences and method calls. The document also defines queues as collections where elements are added to the rear and removed from the front in a first-in, first-out (FIFO) manner. Common queue operations and applications like waiting lists and printer access are also covered. Finally, it discusses implementations of stacks and queues using arrays and how to handle overflow and underflow cases.

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Unit 5 dsa QUEUE

1. Pune Vidyarthi Griha’s COLLEGE OF ENGINEERING, NASHIK – 3. “QUEUE” By Prof. Anand N. Gharu (Assistant Professor) PVGCOE Computer Dept. 01 August 2019 .

2. Introduction of Queue ➢ “A queue is an ordered list in which all insertions are done at one end, called rear and deletions at another end called front“ ➢ Queue when implemented using arrays has some drawbacks which can be avoided by circular queue ➢ Queue is used in many applications such as as simulation, priority queue, job queueetc

3. Introduction of Queue ➢ One of the most common dataprocessing structures ➢ Frequently used in most of the system software's like operating systems, Network and Database implementations and in many more other areas ➢ Very useful in time-sharing and distributed computer systems where many widely distributed users share the system simultaneously

4. Array representation and implementation of queue ➢ An array representation of queue require three entities : 1. An array to hold queue element 2. A variable to hold index of the front element 3. A variable to hold index of the rear element

5. Array representation and implementation of queue

6. Array representation and implementation of queue

7. Array representation and implementation of queue

8. Operation on queue implemented using array

9. Operation on queue implemented using array

10. Operation on queue implemented using array

11. Operation on queue implemented using array

12. Operation on queue implemented using array

13. Queue as an ADT ➢ Create : Create creates an empty queue, Q ➢ Add (i,Q) : Add adds the element i to the rear end of queue, Q and returns the newqueue ➢ Delete (Q) : Delete takes out an element i from the ➢ front end of queue and returns the resulting queue ➢ Front(Q) : Front returns the element i which is at the front position of queue ➢ Is_Empty_Q(Q) : Is_Empty_Q returns true if queue is ➢ empty otherwise returns false

14. Queue as an ADT

15. Queue as an ADT

16. Queue as an ADT

17. STACK VS QUEUE

22. Operation on queue implemented using Linked list

23. Operation on queue implemented using Linked list

24. Operation on queue implemented using Linked list

25. Operation on queue implemented using Linked list

26. Operation on queue implemented using Linked list

27. Operation on queue implemented using Linked list

28. Circular Queue

29. 6-29 Second Approach: Queue as a Circular Array • If we don't fix one end of the queue at index 0, we won't have to shift elements • Circular array is an array that conceptually loops around on itself o The last index is thought to “precede” index 0 o In an array whose last index is n, the location “before” index 0 is index n; the location “after” index n is index 0 • Need to keep track of where the front as well as the rear of the queue are at any given time

30. 6-30 Conceptual Example of a Circular Queue 1 0 12 11 10 1 0 12 11 10 1 0 12 11 10 After 7 enqueues front rear After 5 dequeues front rear After 8 more enqueues front rear

31. 6-31 Implementation of a Queue rear front 5 queue count 8 3 0 1 2 3 4 5 6 7 8 9 10 n-1 n-2 n-3 . .. cq

32. 6-32 A Queue Straddling the End of a Circular Array rear front 4 queue count 2 98 0 1 2 3 4 5 6 7 8 9 10 99 98 97 . .. cq

33. 6-33 Circular Queue Drawn Linearly rear front 4 queue count 2 98 0 4321 96 97 98 99 … Queue from previous slide cq

34. 6-34 Circular Array Implementation • When an element is enqueued, the value of rear is incremented • But it must take into account the need to loop back to index 0: rear = (rear+1) % queue.length; • Can this array implementation also reach capacity?

35. 6-35 Example: array of length 4 What happens? rear front 3 queue count 1 2 0 321 rear front 4 queue count 2 2 0 321 Suppose we try to add one more item to a queue implemented by an array of length 4 cq cq The queue is now full. How can you tell?

36. 6-36 Need to expand capacity… rear front 4 queue count 2 2 0 321 rear front 4 queue count 2 2 0 321 4 765 We can’t just double the size of the array and copy values to the same positions as before: circular properties of the queue will be lost These locations should be in use cq cq

37. 6-37 rear front 4 queue count 6 2 0 321 4 765 We could build the new array, and copy the queue elements into contiguous locations beginning at location front: cq

38. 6-38 rear front 4 queue count 4 0 0 321 4 765 Better: copy the queue elements in order to the beginning of the new array cq

39. 6-39 rear front 5 queue count 5 0 0 321 4 765 New element is added at rear = (rear+1) % queue.length See expandCapacity() in CircularArrayQueue.java cq

45. DeQueue

46. DeQueue

47. DeQueue as an ADT

48. Implementation of DeQueue using linked list

49. C function for deque using circular array

50. C function for deque using circular array

51. Priority Queue