33 Lecture - Priority Queue Using Heap

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33 Lecture

CS301

Midterm & Final Term Short Notes

Priority Queue Using Heap

A priority queue is a data structure that stores a collection of elements where each element has a priority associated with it. Using a heap to implement a priority queue allows for efficient insertion and retrieval of elements with the highest


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  1. What is a priority queue using a heap? A) A queue where elements are arranged in the order they are inserted B) A queue where elements are arranged in ascending order C) A queue where elements are arranged based on their priority D) A queue where elements are arranged in descending order Answer: C

  2. Which operation(s) can be performed on a priority queue? A) Insertion B) Deletion C) Retrieval of the highest priority element D) All of the above Answer: D

  3. What is the time complexity of insertion in a priority queue using a heap? A) O(1) B) O(log n) C) O(n) D) O(n^2) Answer: B

  4. What is the time complexity of retrieval of the highest priority element in a priority queue using a heap? A) O(1) B) O(log n) C) O(n) D) O(n^2) Answer: A

  5. Which data structure is used to implement a priority queue using a heap? A) Array B) Linked list C) Stack D) Queue Answer: A

  6. What is the property of a heap that ensures the highest priority element is always at the top? A) Heap size B) Heap capacity C) Heap order D) Heap property Answer: D

  7. Which type of heap is used to implement a priority queue? A) Max heap B) Min heap C) Both A and B D) Neither A nor B Answer: A

  8. What happens when a new element is inserted into a priority queue using a heap? A) The element is added to the end of the heap B) The element is added to the beginning of the heap C) The element is added to the correct position based on its priority D) None of the above Answer: C

  9. What happens when the highest priority element is removed from a priority queue using a heap? A) The last element is removed B) The first element is removed C) The element in the correct position is removed D) None of the above Answer: C

  10. Which of the following statements is true about a priority queue using a heap? A) The elements are arranged in ascending order B) The time complexity of insertion is O(n) C) The highest priority element is always at the top D) All elements have the same priority Answer: C



Subjective Short Notes
Midterm & Finalterm Prepration
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  1. What is a priority queue using a heap? Answer: A priority queue using a heap is a data structure that stores a collection of elements where each element has a priority associated with it. It allows for efficient insertion and retrieval of elements with the highest priority.

  2. How is a priority queue implemented using a heap? Answer: A priority queue using a heap is implemented using an array-based binary heap data structure. The heap property ensures that the element with the highest priority is always at the top of the heap.

  3. What is the time complexity of insertion in a priority queue using a heap? Answer: The time complexity of insertion in a priority queue using a heap is O(log n).

  4. What is the time complexity of retrieval of the highest priority element in a priority queue using a heap? Answer: The time complexity of retrieval of the highest priority element in a priority queue using a heap is O(1).

  5. How is a new element inserted into a priority queue using a heap? Answer: A new element is inserted into a priority queue using a heap by adding it to the end of the heap and then reorganizing the heap to maintain the heap property.

  6. How is the highest priority element removed from a priority queue using a heap? Answer: The highest priority element is removed from a priority queue using a heap by removing the element at the top of the heap and then reorganizing the heap to maintain the heap property.

  7. What happens if two elements in a priority queue using a heap have the same priority? Answer: If two elements in a priority queue using a heap have the same priority, their order in the heap is determined by their position in the array-based binary heap data structure.

  8. How is the heap property maintained in a priority queue using a heap? Answer: The heap property is maintained in a priority queue using a heap by reorganizing the heap after every insertion or removal operation.

  9. What is the difference between a max heap and a min heap? Answer: A max heap is a binary heap where the element with the highest priority is at the top of the heap, while a min heap is a binary heap where the element with the lowest priority is at the top of the heap.

  10. What is the advantage of using a priority queue using a heap over other data structures? Answer: The advantage of using a priority queue using a heap is that it allows for efficient insertion and retrieval of elements with the highest priority, with a time complexity of O(log n) for insertion and O(1) for retrieval.

A priority queue is a data structure that stores a collection of elements where each element has a priority associated with it. The element with the highest priority is always at the top of the queue, and removal of elements is done in order of priority. A heap is a binary tree-based data structure that is used to implement a priority queue. A heap can be a max heap or a min heap, depending on whether the element with the highest or lowest priority is at the top of the heap, respectively. In a priority queue using a heap, the heap property ensures that the element with the highest priority is always at the top of the heap. The implementation of a priority queue using a heap is based on an array-based binary heap data structure, where the parent node of any element is located at index i/2 and the left and right children are located at indices 2i and 2i+1, respectively. Insertion in a priority queue using a heap is done by adding the new element to the end of the heap and then reorganizing the heap to maintain the heap property. The time complexity of insertion in a priority queue using a heap is O(log n). Retrieval of the highest priority element is done by removing the element at the top of the heap and then reorganizing the heap to maintain the heap property. The time complexity of retrieval of the highest priority element is O(1). A priority queue using a heap is a fundamental concept in data structures and algorithms, and is widely used in computer science. It is used in applications where elements have different priorities, such as scheduling jobs in an operating system, implementing Dijkstra's algorithm for shortest path, and implementing Huffman coding for data compression. In conclusion, a priority queue using a heap is an efficient and widely used data structure for implementing a priority queue. It allows for efficient insertion and retrieval of elements with the highest priority, and is a fundamental concept in data structures and algorithms. Its implementation is based on an array-based binary heap data structure, which ensures that the element with the highest priority is always at the top of the heap.

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