The Levenshtein distance (Edit distance) Problem
Edit distance is a way of quantifying how different two strings are from one another by counting the minimum number of operations required to transform one string into the other.
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Find a subsequence of a given sequence such that the subsequence sum is as high as possible and the subsequence’s elements are in sorted order, from lowest to highest. This subsequence is not necessarily contiguous or unique.
The longest bitonic subsequence problem is to find a subsequence of a given sequence in which the subsequence’s elements are first sorted in increasing order, then in decreasing order, and the subsequence is as long as possible.
The longest increasing subsequence problem is to find a subsequence of a given sequence in which the subsequence’s elements are in sorted order, lowest to highest, and in which the subsequence is as long as possible. This subsequence is not necessarily contiguous or unique.
The Shortest Common Supersequence (SCS) is finding the shortest supersequence Z of given sequences X and Y such that both X and Y are subsequences of Z.
The Shortest Common Supersequence (SCS) is finding the shortest supersequence Z of given sequences X and Y such that both X and Y are subsequences of Z.
The Shortest Common Supersequence (SCS) is finding the shortest supersequence Z of given sequences X and Y such that both X and Y are subsequences of Z.
The Longest Repeating Subsequence (LRS) problem is finding the longest subsequences of a string that occurs at least twice.
The Longest Palindromic Subsequence (LPS) problem is finding the longest subsequences of a string that is also a palindrome.
The longest common substring problem is the problem of finding the longest string (or strings) that is a substring (or are substrings) of two strings.
Given two sequences, print all the possible longest common subsequences present in them.
This post covers a space-optimized function to find the length of the Longest Common Subsequence (LCS) problem.