2010•Fundamenta InformaticaeRequires access

Bit-Parallel Algorithm for the Constrained Longest Common Subsequence Problem

Sebastian Deorowicz

Open publisher page 18 citations

Abstract

The problem of finding a constrained longest common subsequence (CLCS) for the sequences A and B with respect to the sequence P was introduced recently. Its goal is to find a longest subsequence C of A and B such that P is a subsequence of C. Most of the algorithms solving the CLCS problem are based on dynamic programming. Bit-parallelism is a technique of using single bits in a machine word for concurrent computation. We propose the first bit-parallel algorithm computing a CLCS and/or its length which outperforms the other known algorithms in terms of speed.

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What this paper is about

The problem of finding a constrained longest common subsequence (CLCS) for the sequences A and B with respect to the sequence P was introduced recently. Its goal is to find a longest subsequence C of A and B such that P is a subsequence of C. Most of the algorithms solving the CLCS problem are based on dynamic programming. Bit-parallelism is a technique of using single bits in a machine word for concurrent computation. We propose the first bit-parallel algorithm computing a CLCS and/or its length which outperforms the other known algorithms in terms of speed.

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OpenAlex reports 18 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The problem of finding a constrained longest common subsequence (CLCS) for the sequences A and B with respect to the sequence P was introduced recently. Its goal is to find a longest subsequence C of A and B such that P is a subsequence of C. Most of the algorithms solving the CLCS problem are based on dynamic programming. Bit-parallelism is a technique of using single bits in a machine word for concurrent computation. We propose the first bit-parallel algorithm computing a CLCS and/or its length which outperforms the other known algorithms in terms of speed.

Key concepts: Longest common subsequence problem, Longest increasing subsequence, Subsequence, Computer science, Sequence (biology), Parallelism (grammar), Algorithm, Computation

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