Introduction to Heaps Video Lecture | Question Bank for GATE Computer Science Engineering - Computer Science Engineering (CSE)
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FAQs on Introduction to Heaps Video Lecture - Question Bank for GATE Computer Science Engineering - Computer Science Engineering (CSE)
| 1. What is a heap in computer science? |  |
Ans. A heap is a specialized tree-based data structure that satisfies the heap property. It is commonly used to implement priority queues. In computer science, a heap is a complete binary tree where the value of each parent node is either greater than or equal to its child nodes (in a max heap) or lesser than or equal to its child nodes (in a min heap).
| 2. What is the difference between a max heap and a min heap? | |
Ans. The main difference between a max heap and a min heap lies in how the heap property is defined. In a max heap, the value of each parent node is greater than or equal to its child nodes, so the maximum element is always at the root. In contrast, in a min heap, the value of each parent node is lesser than or equal to its child nodes, so the minimum element is always at the root.
| 3. How is a heap represented in memory? | |
Ans. A heap is typically represented using an array-based implementation. The elements of the heap are stored in an array, with the root at index 0, and the child nodes of a parent at indices determined by simple mathematical formulas. This representation allows efficient memory usage and easy access to parent and child nodes.
| 4. What operations can be performed on a heap? | |
Ans. The main operations that can be performed on a heap include insertion, deletion, and retrieval of the maximum or minimum element (depending on whether it is a max heap or min heap). These operations have time complexities of O(log n) in the average and worst cases, where n is the number of elements in the heap.
| 5. What are the applications of heaps in computer science? | |
Ans. Heaps have various applications in computer science, including:
- Implementing priority queues: Heaps are commonly used to efficiently implement priority queues, where elements with higher priorities are dequeued before elements with lower priorities.
- Sorting algorithms: Heapsort is a comparison-based sorting algorithm that uses a heap data structure. It has a worst-case time complexity of O(n log n), making it suitable for large datasets.
- Graph algorithms: Heaps are used in various graph algorithms, such as Dijkstra's shortest path algorithm and Prim's minimum spanning tree algorithm, to efficiently select the next vertex or edge based on their weights or distances.
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Nov 18, 2024 Last updated |
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