Feature/bitap pattern matching

[Kalkwst]

This PR introduces the Bitap algorithm, a powerful string-matching technique renowned for its efficiency in finding exact patterns within text. Bitap leverages bitwise operations to achieve rapid matching, making it particularly well-suited for scenarios where speed is crucial, such as large-scale text processing, search engines, and bioinformatics applications.

The implemented functions, 1FindExactPattern1 and 1FindFuzzyPattern`, provide implementation for both exact matching and fuzzy matching using this algorithm.

Motivation

• Speed Optimization: Bitap offers a substantial performance improvement over naïve string search approaches, especially when dealing with longer patterns or large datasets.
• Versatility: While primarily designed for exact pattern matching, Bitap can be extended to handle fuzzy matching with minor modifications.
• Reduced Complexity: Bitap's elegant bit-parallel approach can simplify code compared to other string-matching algorithms.

How Bitap Works (Simplified)

• Pattern Preprocessing: A bitmask is created for the pattern, representing each character's presence or absence.
• Text Scanning: The algorithm iterates over the text, maintaining a "state" register. Bitwise operations are used to update this state based on the current character.
• Match Detection: When the state register indicates a match, the corresponding index is returned.

Pros

• Exceptional Speed: Outperforms naïve string search in most cases.
• Compact Implementation: Relatively straightforward to code compared to some other algorithms.
• Low Memory Usage: Bitap primarily relies on bitwise operations, using minimal memory.

Cons

• Limited to Exact Matching: While fuzzy matching extensions exist, they can be less efficient than dedicated fuzzy search algorithms.
• Preprocessing Overhead: Bitap requires a preprocessing step to create the pattern mask.
• Character Set Limitations: The classic Bitap algorithm assumes a fixed character set (e.g., ASCII).

Use Cases

• Text Editors: Implementing fast search functionality.
• Search Engines: Efficiently indexing and retrieving text data.
• Bioinformatics: Quickly identifying patterns in DNA or protein sequences.
• Network Intrusion Detection: Scanning network traffic for malicious patterns.

See also

Bitap Algorithm - Wikipedia

---

• I have performed a self-review of my code
• My code follows the style guidelines of this project
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes
• Comments in areas I changed are up to date
• I have added comments to hard-to-understand areas of my code
• I have made corresponding changes to the README.md

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 94.88%. Comparing base (327af3d) to head (7ab8ba1).

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #458      +/-   ##
==========================================
+ Coverage   94.84%   94.88%   +0.03%     
==========================================
  Files         234      235       +1     
  Lines        9897     9967      +70     
  Branches     1393     1408      +15     
==========================================
+ Hits         9387     9457      +70     
  Misses        392      392              
  Partials      118      118              

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

[siriak]

Looks good, thanks a lot for contributing this algorithm!