Fastest Searching Algorithm | GFact

Pattern searching is a critical operation in the field of computer science, Its applications range from text processing and DNA sequencing to image recognition and data mining. As data sizes grow exponentially, the demand for faster pattern-searching algorithms has only grown.

Which is the Fastest Searching Algorithm?

One of the best algorithms is the “Boyer-Moore“ algorithm. It utilizes a two-step approach, utilizing a “bad character heuristic” and a “good suffix heuristic.” By skipping unnecessary comparisons and maximizing the steps taken for each comparison, Boyer-Moore can significantly reduce the number of operations required, making it one of the fastest pattern-searching algorithms out there.

Why is Boyer-Moore the fastest searching algorithm?

The Boyer–Moore algorithm uses information gathered during the preprocessing step to skip text sections, resulting in a lower constant factor than many other string search algorithms. In general, the algorithm runs faster as the pattern length increases.

Comparison of Boyer-Moore with other Pattern Searching Algorithms

If the Length of the text string is N and the length of the pattern string is M then the following is the complexity analysis chart for different pattern-searching algorithms:

Algorithm	Time Complexity [Worst Case]	Time Complexity [Best Case]	Auxiliary Space Complexity
Naïve Algorithm	O( N * M )	O(M)	O( 1 )
KMP Algorithm	O( M + N )	O( M )	O( M )
Z Algorithm	O( M + N )	O( M + N )	O( M + N )
Boyer Moore Algorithm	O(N*M)	Ω(N/M)	O(M + | Σ | )
Rabin Karo Algorithm	O( N + M )	O( M )	O( M )