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cs updates on arXiv.org

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Selective Memoization for Efficient Backtracking Regular ...
[Submitted on 25 Jun 2026] · 2026-06-26 · via cs updates on arXiv.org

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Abstract:Backtracking regular expression matchers are widely used due to their expressive power but may exhibit exponential worst-case matching time. Memoization provides a principled method for eliminating redundant computation and ensuring linear matching time, but full memoization is memory-intensive and impractical. We introduce the Minimum Feedback Node (MFN) memoization scheme, a selective memoization strategy based on computing a minimum feedback vertex set of an automaton. We establish relationships with existing memoization schemes and analyze their behaviour under both Thompson and Glushkov automaton constructions.

Submission history

From: EPTCS [view email] [via EPTCS proxy]
[v1] Thu, 25 Jun 2026 07:13:03 UTC (259 KB)