Application of Divide & Conquer in Quick Sort

QuickSort is a sorting algorithm based on the Divide and Conquer algorithm that picks an element as a pivot and partitions the given array around the picked pivot by placing the pivot in its correct position in the sorted array.

The key process in quickSort is a partition(). The target of partitions is to place the pivot (any element can be chosen to be a pivot) at its correct position in the sorted array and put all smaller elements to the left of the pivot, and all greater elements to the right of the pivot.
Partition is done recursively on each side of the pivot after the pivot is placed in its correct position and this finally sorts the array.

Choice of Pivot:

There are many different choices for picking pivots. 

Time Complexity:

  • Worst Case: O(n^2), occurs when the pivot selection consistently results in unbalanced partitions.
  • Best Case: O(n log n), occurs when the pivot selection consistently results in balanced partitions.
  • Average Case: O(n log n)

Space Complexity: O(log n), for the recursive call stack.

Divide and Conquer Notes for GATE Exam [2024]

Those preparing for the GATE (Graduate Aptitude Test in Engineering) exam in 2024 face many algorithmic challenges. Among the various algorithmic paradigms, “Divide and Conquer” stands out as a powerful approach to problem-solving. In this comprehensive guide for the GATE Exam, Divide and Conquer, and its applications will be explored through a range of important topics. These notes aim to provide a solid foundation for mastering these concepts in preparation for the upcoming GATE exam.

Table of Content

  • Introduction to Divide and Conquer
  • Application of Divide & Conquer in Binary Search
  • Application of Divide & Conquer in Merge Sort
  • Application of Divide & Conquer in Quick Sort
  • Standard Problems that uses Divide and Conquer Algorithm
  • Advantages of Divide and Conquer Algorithm
  • Disadvantages of Divide and Conquer Algorithm
  • Previously Asked GATE Questions on Divide and Conquer

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Introduction to Divide and Conquer:

Divide and Conquer is an algorithmic paradigm in which the problem is solved using the Divide, Conquer, and Combine strategy....

Application of Divide & Conquer in Binary Search:

Binary Search is a search algorithm that efficiently finds a target value within a sorted array. It repeatedly divides the search space in half until the target is found or the search space is empty....

Application of Divide & Conquer in Merge Sort:

Merge Sort is a divide-and-conquer sorting algorithm that recursively divides an array into two halves, sorts each half, and then merges them to produce a sorted array....

Application of Divide & Conquer in Quick Sort:

QuickSort is a sorting algorithm based on the Divide and Conquer algorithm that picks an element as a pivot and partitions the given array around the picked pivot by placing the pivot in its correct position in the sorted array....

Standard Problems that uses Divide and Conquer Algorithm:

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Advantages of Divide and Conquer Algorithm:

It divides the entire problem into subproblems thus it can be solved parallelly ensuring multiprocessing Efficiently uses cache memory without occupying much space. Reduces time complexity of the problem....

Disadvantages of Divide and Conquer Algorithm:

It may crash the system if the recursion is performed rigorously. The process of dividing the problem into subproblems and then combining the solutions can require additional time and resources. Complexity: Dividing a problem into smaller subproblems can increase the complexity of the overall solution. When working with large data sets, the memory requirements for storing the intermediate results of the subproblems can become a limiting factor....

Previously Asked GATE Questions on Divide and Conquer:

Question 1: Which of the following algorithms is NOT a divide & conquer algorithm by nature?...

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