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DOI: 10.4230/LIPIcs.CPM.2026.15

Improved Approximation Ratios for the Shortest Common Superstring Problem with Reverse Complements

Authors: Ryosuke Yamano and Tetsuo Shibuya

Published in: LIPIcs, Volume 369, 37th Annual Symposium on Combinatorial Pattern Matching (CPM 2026)

Abstract

The Shortest Common Superstring (SCS) problem asks for the shortest string that contains each of a given set of strings as a substring. Its reverse-complement variant, the Shortest Common Superstring problem with Reverse Complements (SCS-RC), naturally arises in bioinformatics applications, where for each input string, either the string itself or its reverse complement must appear as a substring of the superstring. The well-known MGREEDY algorithm for the standard SCS constructs a superstring by first computing an optimal cycle cover on the overlap graph and then concatenating the strings corresponding to the cycles, while its refined variant, TGREEDY, further improves the approximation ratio. Although the original 4- and 3-approximation bounds of these algorithms have been successively improved for the standard SCS, no such progress has been made for the reverse-complement setting. A previous study extended MGREEDY to SCS-RC with a 4-approximation guarantee and briefly suggested that extending TGREEDY to the reverse-complement setting could achieve a 3-approximation. In this work, we strengthen these results by proving that the extensions of MGREEDY and TGREEDY to the reverse-complement setting achieve 3.75- and 2.875-approximation ratios, respectively. Our analysis extends the classical proofs for the standard SCS to handle the bidirectional overlaps introduced by reverse complements. These results provide the first formal improvement of approximation guarantees for SCS-RC, with the 2.875-approximate algorithm currently representing the best known bound for this problem.

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Ryosuke Yamano and Tetsuo Shibuya. Improved Approximation Ratios for the Shortest Common Superstring Problem with Reverse Complements. In 37th Annual Symposium on Combinatorial Pattern Matching (CPM 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 369, pp. 15:1-15:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{yamano_et_al:LIPIcs.CPM.2026.15,
  author =	{Yamano, Ryosuke and Shibuya, Tetsuo},
  title =	{{Improved Approximation Ratios for the Shortest Common Superstring Problem with Reverse Complements}},
  booktitle =	{37th Annual Symposium on Combinatorial Pattern Matching (CPM 2026)},
  pages =	{15:1--15:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-420-8},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{369},
  editor =	{Bille, Philip and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2026.15},
  URN =		{urn:nbn:de:0030-drops-259412},
  doi =		{10.4230/LIPIcs.CPM.2026.15},
  annote =	{Keywords: Shortest Common Superstring, Approximation Algorithms, DNA Sequencing}
}

Document

DOI: 10.4230/LIPIcs.WABI.2025.21

Linear-Space Subquadratic-Time String Alignment Algorithm for Arbitrary Scoring Matrices

Authors: Ryosuke Yamano and Tetsuo Shibuya

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)

Abstract

Theoretically, the fastest algorithm by Crochemore et al. for computing the alignment of two given strings of size n over a constant alphabet takes O(n²/log n) time. The algorithm uses Lempel–Ziv parsing to divide the dynamic programming matrix into blocks and utilizes the repetitive structure. It is the only previously known subquadratic-time algorithm that can handle scoring matrices of arbitrary weights. However, this algorithm takes O(n²/log n) space, and reducing the space while preserving the time complexity has been an open problem for more than 20 years. We present a solution to this issue by achieving an O(n) space algorithm that maintains O(n²/log n) time. The classical refinement by Hirschberg reduces the space complexity of the textbook O(n²) algorithm to O(n) while preserving the quadratic time. However, applying this technique to the algorithm of Crochemore et al. has been considered challenging because their method requires O(n² / log n) space even when computing only the alignment score. Our modification enables the application of Hirschberg’s refinement, allowing traceback computation in O(n) space while preserving the O(n² / log n) overall time complexity. Our algorithm can be applied to both global and local string alignment problems.

Cite as

Ryosuke Yamano and Tetsuo Shibuya. Linear-Space Subquadratic-Time String Alignment Algorithm for Arbitrary Scoring Matrices. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 21:1-21:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{yamano_et_al:LIPIcs.WABI.2025.21,
  author =	{Yamano, Ryosuke and Shibuya, Tetsuo},
  title =	{{Linear-Space Subquadratic-Time String Alignment Algorithm for Arbitrary Scoring Matrices}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{21:1--21:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.21},
  URN =		{urn:nbn:de:0030-drops-239479},
  doi =		{10.4230/LIPIcs.WABI.2025.21},
  annote =	{Keywords: String alignment, dynamic programming, linear space algorithms}
}

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Documents authored by Yamano, Ryosuke

Improved Approximation Ratios for the Shortest Common Superstring Problem with Reverse Complements

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Linear-Space Subquadratic-Time String Alignment Algorithm for Arbitrary Scoring Matrices

Abstract

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