Levenshtein Distance
Levenshtein distance is a string metric for measuring the difference between two sequences, defined as the minimum number of single-character edits (insertions, deletions, or substitutions) required to change one word into another. It is widely used in fields like computational linguistics, bioinformatics, and data cleaning to quantify similarity or dissimilarity between strings. The concept is named after Vladimir Levenshtein, who introduced it in 1965.
Developers should learn Levenshtein distance when working on tasks involving fuzzy string matching, spell checking, or data deduplication, as it provides a robust way to handle typos, variations, or errors in text data. It is essential in applications like search engines, natural language processing, and database record linkage, where exact matches are insufficient and approximate matching improves user experience and data quality.