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...

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Published inInternational Research Journal on Advanced Engineering and Management (IRJAEM) Vol. 3; no. 8; pp. 2741 - 2746
Main Author Prof.Mrs. Tejaswini.A. Puranik
Format Journal Article
LanguageEnglish
Published 26.08.2025
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ISSN2584-2854
2584-2854
DOI10.47392/IRJAEM.2025.0430

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Summary: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.
ISSN:2584-2854
2584-2854
DOI:10.47392/IRJAEM.2025.0430