'Average case time complexity' presentation slideshows

CS5263 Bioinformatics

CS5263 Bioinformatics. Lecture 9-10 Exact String Matching Algorithms. Overview. Pair-wise alignment Multiple alignment Commonality: allowing errors when comparing strings Two sub-problems: How to score an alignment with errors How to find an alignment with the best score

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Data Structures Review Session

Data Structures Review Session. Ramakrishna, PhD student. Grading Assistant for this course. Quick Sort Review. p. p. numbers greater than or equal to p. numbers less than p. PARTITIONING. A key step in the Quick sort algorithm is partitioning the array

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Analyzing sorting algorithms

Analyzing sorting algorithms. Recall that T(n) represents the time required for an algorithm to process input of size n. For a sorting algorithm, T(n) represents the time needed to sort. this time may be the worst-case time, the average-case time, or something else.

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Analysis of algorithms

Analysis of algorithms. Best case: easiest Worst case Average case: hardest . input: 7,5,1,4,3 7, 5 ,1,4,3 5,7, 1 ,4,3 1,5,7, 4 ,3 1,4,5,7, 3 1,3,4,5,7. Straight insertion sort. M: # of data movements in straight insertion sort 1 5 7 4 3

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Chapter 7: Sorting

Chapter 7: Sorting. Insertion Sort. Shell Sort. Heap Sort. Merge Sort. Quick Sort. Best Case Sorting Algorithm Analysis. CS 340. Page 112. Sorting. While sorting an array of elements is itself a significant problem, examining this problem serves several other purposes:

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Algorithm

Algorithm. An algorithm is a finite set of steps required to solve a problem. An algorithm must have following properties: Input: An algorithm must have zero or more quantities as input whcih are externally supplied. Output:

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Sorting

Sorting. A fundamental operation in computer science (many programs need to sort as an intermediate step). Many sorting algorithms have been developed Choose a criteria which is used to order data

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