Category Archives: Algorithms

Linear Search vs Binary Search

Prerequisite: Linear Search Binary Search A linear search scans one item at a time, without jumping to any item . The worst case complexity is  O(n), sometimes known an O(n) search Time taken to search elements keep increasing as the number of elements are increased. A binary search however, cut down your search to half as… Read More »



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Time Complexities of all Sorting Algorithms

Following is a quick revision sheet that you may refer at last minute   Algorithm Time Complexity   Best Average Worst Selection Sort Ω(n^2) θ(n^2) O(n^2) Bubble Sort Ω(n) θ(n^2) O(n^2) Insertion Sort Ω(n) θ(n^2) O(n^2) Heap Sort Ω(n log(n)) θ(n log(n)) O(n log(n)) Quick Sort Ω(n log(n)) θ(n log(n)) O(n^2) Merge Sort Ω(n log(n)) θ(n… Read More »



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Triangular Numbers

A number is termed as triangular number if we can represent it in the form of triangular grid of points such that the points form an equilateral triangle and each row contains as many points as the row number, i.e., the first row has one point, second row has two points, third row has three… Read More »



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Sorting Strings using Bubble Sort

Given an array of strings arr[]. Sort given strings using Bubble Sort and display the sorted array. In Bubble Sort, the two successive strings arr[i] and arr[i+1] are exchanged whenever arr[i]> arr[i+1]. The larger values sink to the bottom and hence called sinking sort. At the end of each pass, smaller values gradually “bubble” their… Read More »



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Binary Search for Rational Numbers without using floating point arithmetic

A rational is represented as p/qb, for example 2/3. Given a sorted array of rational numbers, how to search an element using Binary Search. Use of floating point arithmetic is not allowed. Example: Input: arr[] = {1/5, 2/3, 3/2, 13/2} x = 3/2 Output: Found at index 2 We strongly recommend you to minimize your… Read More »



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