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MFCS 2021

Sublinear Algorithms for Edit Distance (Invited Talk)

Conference Paper Accepted Paper Algorithms and Complexity · Theoretical Computer Science

Abstract

The edit distance is a way of quantifying how similar two strings are to one another by counting the minimum number of character insertions, deletions, and substitutions required to transform one string into the other. A simple dynamic programming computes the edit distance between two strings of length n in O(n²) time, and a more sophisticated algorithm runs in time O(n+t²) where t is the distance (Landau, Myers and Schmidt, SICOMP 1998). In pursuit of obtaining faster running time, the last couple of decades have seen a flurry of research on approximating edit distance, including polylogarithmic approximation in near-linear time (Andoni, Krauthgamer and Onak, FOCS 2010), and a constant-factor approximation in subquadratic time (Chakrabarty, Das, Goldenberg, Koucký and Saks, FOCS 2018). In this talk, we will discuss recent progress that goes beyond linear time, and studies sublinear time algorithms for edit distance. We will also discuss the role preprocessing might play in designing fast algorithms. This is a joint work with Elazar Goldenberg, Tomasz Kociumaka, Robert Krauthgamer, and Aviad Rubinstein.

Authors

Keywords

  • Edit distance
  • sublinear algorithms
  • string processing

Context

Venue
International Symposium on Mathematical Foundations of Computer Science
Archive span
1973-2025
Indexed papers
3045
Paper id
1111587590701412242
v2026.09.13