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Showing posts with label Data Structures. Show all posts
Showing posts with label Data Structures. Show all posts

# Multiple choices questions in DSA, Interview questions in DSA, Data Structures and Algorithms solved questions, Which sorting algorithm is best? Why heap sort is comparatively best algorithm if memory is the major concern? How much auxiliary spaces need for bubble sort, heap sort and insertion sort? Why merge sort is not a best option if memory is a major concern?

## DSA solved MCQ - Which sorting technique is best in terms of time complexity and auxiliary space used?

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Answer: (b) Heap sort

Among the given sorting algorithms, heap sort is the best option if memory is a real concern for you.

Heap sort uses O(1) auxiliary space (i.e., constant) since it is an in-place sorting algorithm. Also, the worst case running complexity is O(n log n). With a small worst-case running time and efficient space usage, heap sort is the best option among the others.

On the other hand, merge sort takes up O(n) auxiliary space. Though the auxiliary space requirement for both bubble and insertion sort are constant (O(1)),  the worst case time complexity is O(n2) for both the algorithms.

 Algorithm Auxiliary space required Worst case time complexity Heap sort O(1) O(n log n) Merge sort O(n) O(n log n) Bubble sort O(1) O(n2) Insertion sort O(1) O(n2)

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Why merge sort is not a best option if memory is a major concern for you? Merge sort is not a good option if memory is a major concern because it needs O(n) auxiliary memory space to store the merged sub-array.

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