Reducing approximate Longest Common Subsequence to approximate Edit Distance
Aviad Rubinstein, Zhao Song
Abstract
Given a pair of n-character strings, the problems of computing their Longest Common Subsequence and Edit Distance have been extensively studied for decades. For exact algorithms, LCS and Edit Distance (with character insertions and deletions) are equivalent; the state of the art running time is (almost) quadratic in n, and this is tight under plausible fine-grained complexity assumptions. But for approximation algorithms the picture is different: there is a long line of works with improved approximation factors for Edit Distance, but for LCS (with binary strings) only a trivial 1/2-approximation was known. In this work we give a reduction from approximate LCS to approximate Edit Distance, yielding the first efficient (1/2 + ϵ)-approximation algorithm for LCS for some constant ϵ > 0.
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Install the CLIlune papers fulltext 72e71724-5018-4d59-9c50-9ad404d178cdCited by top-tier papers8
- Edit Distance in Near-Linear Time: it's a Constant FactorAlexandr Andoni, Negev Shekel NosatzkiFOCS 2020 · 28 citations
- Does preprocessing help in fast sequence comparisons?Elazar Goldenberg, Aviad Rubinstein, Barna SahaSTOC 2020 · 15 citations
- Improved Algorithms for Edit Distance and LCS: Beyond Worst CaseMahdi Boroujeni, Masoud Seddighin, Saeed SeddighinSODA 2020 · 8 citations
- How Compression and Approximation Affect Efficiency in String Distance MeasuresArun Ganesh, Tomasz Kociumaka, Andrea Lincoln, Barna SahaSODA 2022 · 7 citations
- Approximation Schemes for Edit Distance and LCS in Quasi-Strongly Subquadratic TimeXiao Mao, Aviad RubinsteinSTOC 2026 · 4 citations
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