Performance Analysis of Sorting and Searching Algorithms

In computer science, the efficiency of algorithms is a critical consideration for optimizing performance. The time and space complexity of sorting and searching algorithms, which are essential to a variety of computational tasks, is frequently the basis for evaluation. Time complexity refers to the amount of time an algorithm takes to complete as a function of the input size, while space complexity indicates the amount of memory the algorithm requires. Bubble Sort, Selection Sort, Merge Sort, and Quick Sort are just a few of the common sorting algorithms included in this investigation. All of these algorithms have time complexities ranging from O(n2) to O (n log n). Similarly, searching algorithms such as Linear Search and Binary Search are examined, with complexities from O(n) to O (log n) depending on the data structure and the algorithm used.