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https://github.com/sunesimonsen/ukkonen
Ukkonen's Approximate String Matching algorithm
https://github.com/sunesimonsen/ukkonen
Last synced: 1 day ago
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Ukkonen's Approximate String Matching algorithm
- Host: GitHub
- URL: https://github.com/sunesimonsen/ukkonen
- Owner: sunesimonsen
- License: mit
- Created: 2017-11-02T08:38:38.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2024-09-03T15:57:02.000Z (30 days ago)
- Last Synced: 2024-09-15T09:02:48.285Z (18 days ago)
- Language: JavaScript
- Homepage:
- Size: 1.66 MB
- Stars: 127
- Watchers: 7
- Forks: 4
- Open Issues: 4
-
Metadata Files:
- Readme: Readme.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# Ukkonen - Approximate String Matching
[](https://badge.fury.io/js/ukkonen)
[](https://github.com/sunesimonsen/ukkonen/actions/workflows/ci.yml)
This project implements the [Approximate String Matching algorithm by Esko Ukkonen](https://www.sciencedirect.com/science/article/pii/S0019995885800462) extended with ideas from [An Extension of Ukkonen's Enhanced Dynamic Programming ASM Algorith by Hal Berghel and David Roach](http://berghel.net/publications/asm/asm.pdf).
Ukkonen's algorithm is very competitive with the [Levenshtein distance](https://en.wikipedia.org/wiki/Levenshtein_distance) and for longer strings it is much more performant than Levenshtein distance.
In addition to being a competitive alternative to Levenshtein distance, Ukkonen's algorithm also allows you to provide a threshold for the distance which increases the performance even more for texts that are longer than the threshold.
Above you can see the different of using Levenshtein distance and Ukkonen's algorithm for matching sub-trees when diffing HTML.
## Install
```sh
npm install --save ukkonen
```
## Usage
You can find the distance between the strings `Ukkonen` and `Levenshtein` the following way:
```js
var ukkonen = require("ukkonen");
assert.equal(ukkonen("Ukkonen", "Levenshtein"), 8);
```
If you want to limit the distance by a given threshold:
```js
var ukkonen = require("ukkonen");
assert.equal(ukkonen("Ukkonen", "Levenshtein", 6), 6);
assert.equal(ukkonen("Ukkonen", "Levenshtein", 10), 8);
```
## Platform support
The library is ES6 and will work with any JavaScript bundler in the browser as well as Node versions with ES6 support.
## Benchmark
I have benchmarked the library against [the fastest Levenshtein distance implementation on NPM](https://github.com/sindresorhus/leven).
```
Running benchmarks with 1000 iterations
# ukkonen: Edit distance one word (14 examples)
ok ~18 ms (0 s + 17993165 ns)
# leven: Edit distance one word (14 examples)
ok ~13 ms (0 s + 13155407 ns)
# ukkonen: Edit distance on sentence with small differences
ok ~1.66 ms (0 s + 1656841 ns)
# leven: Edit distance on sentence with small differences
ok ~7.23 ms (0 s + 7233814 ns)
# ukkonen: Edit distance on paragraphs with small differences
ok ~5.37 ms (0 s + 5367561 ns)
# leven: Edit distance on paragraphs with small differences
ok ~416 ms (0 s + 416468504 ns)
# ukkonen: Edit distance on longer texts with small differences
ok ~10 ms (0 s + 10305586 ns)
# leven: Edit distance on longer texts with small differences
ok ~1.7 s (1 s + 703731130 ns)
# ukkonen: Edit distance on longer texts with many differences
ok ~3.28 s (3 s + 280166305 ns)
# leven: Edit distance on longer texts with many differences
ok ~2.52 s (2 s + 519432479 ns)
# ukkonen: Edit distance on longer texts with small differences and a threshold of 20
ok ~9.69 ms (0 s + 9691021 ns)
# leven: Edit distance on longer texts with small differences and a threshold of 20
ok ~1.61 s (1 s + 610079082 ns)
# ukkonen: Edit distance on longer texts with many differences and a threshold of 40
ok ~15 ms (0 s + 15225792 ns)
# leven: Edit distance on longer texts with many differences and a threshold of 40
ok ~2.54 s (2 s + 539519721 ns)
```
## Acknowledgements
Obviously the authors of the papers describing the algorithm Esko Ukkonen, Hal Berghel and David Roach.
I stole a lot of ideas from [Sindre Sorhus](https://github.com/sindresorhus)'s [leven](https://github.com/sindresorhus/leven) library and I also used it to test my implementation against.
## License
[MIT © Sune Simonsen](./LICENSE)