Pattern Matching in Strings
Understand how to find all occurrences of a pattern string within a larger text using pattern matching. Explore the naive algorithm and learn the limitations it has. Discover how advanced algorithms like Knuth-Morris-Pratt, Boyer-Moore, Rabin-Karp, and the Z-algorithm improve efficiency by reducing redundant comparisons. Gain practical JavaScript implementation knowledge while building a foundation in essential string search techniques.
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.
If all characters match, the pattern has been found at that position. If any character does not match, the attempt fails, and the search moves one position to the right.
This is called the naive algorithm, or the brute-force approach. It is the first solution most people think of, and understanding it well is the right starting point before moving to more sophisticated methods.
How it works
The algorithm follows a simple repeated process:
Let the
textbe the larger string and thepatternbe the smaller string.Consider each valid starting position in the
text(starting from index ...