Americas, Special Report, News

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Runtime grows logarithmically in proportion to n. Runtime grows directly in proportion to n. Runtime grows in proportion to n. Runtime grows quicker than previous all based on n. Runtime grows even faster than polynomial algorithm based on n. Where, n is the input size and c is a positive constant. Some of the examples of all those types of algorithms (in worst-case scenarios) are mentioned below: ? Logarithmic algorithm - O(logn) - Binary Search. Linear algorithm - O(n) - Linear Search. Superlinear algorithm - O(nlogn) - Heap Sort, Merge Sort. Strassen’s Matrix Multiplication, Bubble Sort, Selection Sort, Insertion Sort, Bucket Sort. Factorial algorithm - O(n!) - Determinant Expansion by Minors, Brute force Search algorithm for Traveling Salesman Problem. The performances (Runtimes) of different orders of algorithms separate rapidly as n (the input size) gets larger. Memory Footprint Analysis of AlgorithmsFor performance analysis of an algorithm, runtime measurement is not only relevant metric but also we need to consider the memory usage amount of the program.




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