Pattern Matching in Strings
Understand the naive pattern matching algorithm for searching a substring in a text by checking every valid position. Explore how this method works and its limitations. Discover advanced algorithms like Knuth-Morris-Pratt, Boyer-Moore, Rabin-Karp, and the Z-algorithm that improve efficiency by reducing redundant comparisons in string pattern matching, all implemented in Go.
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A recurring problem in computing is determining whether a short string appears somewhere inside a longer one. This comes up in text editors searching for a word, antivirus software scanning for known signatures, DNA analysis looking for a genetic sequence, and search engines matching queries against documents. The short string being searched for is called the pattern, and the longer string being searched through is called the text.
Formally, the problem is: given a text of length n and a pattern of length m, find all positions in the text where the pattern occurs.
The naive approach
The most natural way to solve this problem requires no clever insight. The idea is to check every possible position in the text where the pattern could begin, and at each position, compare the pattern against the corresponding characters in the text one by one. ...