1. CMPT 225
Lecture 8 – Queue

2. Last Lecture We saw how to … Describe Stack
Define public interface of Stack ADT
Design and implement Stack ADT using various data structures
Compare and contrast these various implementations using Big O notation
Give examples of real-life applications (problems) where we could use Stack to solve the problem
Solve problems using Stack ADT

3. Learning Outcomes
At the end of this lecture, a student will be able to:
Describe Queue
Define public interface of Queue ADT
Design and implement Queue ADT using various data structures
Compare and contrast these various implementations using Big O notation
Give examples of real-life applications (problems) where we could use Queue to solve the problem
Solve problems using Queue ADT

4. Today’s menu
Introducing another linear data collection -> Queue

5. Queue What can we do with a Queue?
Source:

6. What characterizes a Queue?
Only allows elements to be inserted at one end -> back and removed at the other -> front
Access to other elements in a Queue is not allowed
FIFO / LILO
Fair: no starvation -> every element in the queue is processed
Linear data collection
Not a “general-purpose” ADT

7. Step 2 – Design - Queue operations
isEmpty: Is the queue empty?
enqueue: Insert element at back of queue
dequeue: Remove front element of queue
peek: Retrieve front element of queue (but does not remove the element)
dequeueAll: Remove all element from queue

8. Step 2 – Design – Queue public interface – Contract - 1
NOTE: Expressed in C++ and using template Class invariant: FIFO / LILO // Description: Returns true if this Queue is empty otherwise false. // Time Efficiency: O(1) bool isEmpty( ) const; // Description: Adds a new element to the back of this Queue. // Returns true if the addition is successful otherwise false. bool enqueue(const ElementType& newElement);

9. Step 2 – Design – Queue public interface – Contract - 2
// Description: Removes the front element of this Queue.
// Returns true if the removal is successful otherwise false.
// Precondition: The Queue is not empty.
// Time Efficiency: O(1)
bool dequeue( );
Alternative:
// Description: Removes and returns the front element of this Queue.
// Exceptions: Throws EmptyQueueException if this Queue is empty.
ElementType dequeue( ) throw(EmptyQueueException);

10. Step 2 – Design – Queue public interface – Contract - 3
// Description: Removes all elements from this Queue. // Returns true if the removal is successful otherwise false. // Precondition: The Queue is not empty. bool dequeuAll( ); // Description: Returns the front element of this Queue. // Postcondition: This Queue is unchanged. // Exceptions: Throws EmptyQueueException if this Queue is empty. // Time Efficiency: O(1) ElementType peek( ) const throw(EmptyQueueException);

11. Keep in mind …
When we design the underlying data structure of our Queue
We need to decide where front and back are located in our underlying data structure

12. Step 3 - Implementing Queue as an ADT
Array-based implementation

13. Step 3 - Implementing Queue as an ADT
Link-based implementation

14. Step 3 - Implementing Queue as an ADT
List ADT-based implementation
See the List ADT-based implementation of the Stack ADT class from the lecture notes on Stack
From this example, can we do the same with the Queue ADT class, i.e., implement its public methods using the public methods of the List ADT class?

15. Queue ADT - Comparing both its implementations
Time efficiency of Queue ADT’s operations (worst case scenario) expressed using the Big O notation
Operations
array-based
link-based
List ADT-based
isEmpty
push
pop
peek
popAll

16. When a Queue is appropriate
Examples of problem statements that would most appropriately be solved using a data collection Queue ADT class
Pipeline architecture: When module A’s output is module B’s input in a asynchronous fashion or when module B reads its input at a lower rate than module A produces its output -> queue used as a buffer
E.g.: Print queue, keyboard buffer
Server requests: Instant messaging servers queue up incoming messages
Database requests
Operating systems often use queues to schedule CPU jobs

17. √ Learning Check We can now … Describe Queue
Define public interface of Queue ADT
Design and implement Queue ADT using various data structures
Compare and contrast these various implementations using Big O notation
Give examples of real-life applications (problems) where we could use Queue to solve the problem
Solve problems using Queue ADT

18. Next Lecture
Sorting algorithms