Damerau-Levenshtein Distance: Measures similarity between strings accounting for insertions, deletions, substitutions, and transpositions
Normalized Scoring: Calculates similarity score as distance / MAX(queryLength, lineLength) for fair comparison regardless of string lengths
Sorted Output: Results are sorted by similarity score (best matches first)
Efficient Processing: Handles large input streams with dynamic memory allocation

Building

Prerequisites

GCC compiler
Make (optional)

Compilation

Using Make:

make

Or directly with GCC:

gcc -o fuzzy-match fuzzy-match.c -lm

Usage

fuzzy-match <query> < input.txt

or pipe input from another command:

echo -e "apple\napple pie\norange\nbanana\nappl" | fuzzy-match "apple"

Output Format

Each line is printed with its similarity score (lower is more similar):

0.0000	apple
0.2000	appl
0.5000	apple pie
0.6667	banana
1.0000	orange

Examples

Basic matching

$ echo -e "cat\ncar\ndog\nhat" | fuzzy-match "cat"
0.0000	cat
0.3333	car
0.6667	hat
1.0000	dog

Matching with typos

$ echo -e "programming\nprograming\nprogram\nprogamming" | fuzzy-match "programming"
0.0000	programming
0.0909	programing
0.1818	progamming
0.3333	program

Algorithm

The program implements the Damerau-Levenshtein distance algorithm, which measures the minimum number of single-character edits (insertions, deletions, substitutions, and transpositions) needed to transform one string into another.

The similarity score is normalized to account for string length differences:

similarity_score = damerau_levenshtein_distance / MAX(query_length, line_length)

Installation

Install to system PATH:

make install

Uninstall:

make uninstall

Cleaning

Remove compiled binaries:

make clean

License

This project is licensed under the GNU General Public License, version 3. See LICENSE for the full text.