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Superset Generation on Decision Diagrams

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WALCOM: Algorithms and Computation (WALCOM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8973))

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Abstract

Generating all supersets from a given set family is important, because it is closely related to identifying cause-effect relationship. This paper presents an efficient method for superset generation by using the compressed data structures BDDs and ZDDs effectively. We analyze the size of a BDD that represents all supersets. As a by-product, we obtain a non-trivial upper bound for the size of a BDD that represents a monotone Boolean function in a fixed variable ordering.

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Author information

Authors and Affiliations

  1. Graduate School of Information Systems, The University of Electro-Communications, Chofu, Japan

    Takahisa Toda

  2. ERATO MINATO Discrete Structure Manipulation System Project, Japan Science and Technology Agency, Hokkaido University, Sapporo, Japan

    Shogo Takeuchi, Koji Tsuda & Shin-ichi Minato

  3. Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan

    Koji Tsuda

  4. Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan

    Koji Tsuda

  5. Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan

    Shin-ichi Minato

Authors
  1. Takahisa Toda
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  2. Shogo Takeuchi
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  3. Koji Tsuda
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  4. Shin-ichi Minato
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Editor information

Editors and Affiliations

  1. Department of CSE, BUET, ECE Building, West Palasi, 1205, Dhaka, Bangladesh

    M. Sohel Rahman

  2. The Advanced Algorithms Research Laboratory, The University of Electro-Communications, Chofugaoka 1-5-1, 182-8585, Chofu, Tokyo, Japan

    Etsuji Tomita

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© 2015 Springer International Publishing Switzerland

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Toda, T., Takeuchi, S., Tsuda, K., Minato, Si. (2015). Superset Generation on Decision Diagrams. In: Rahman, M.S., Tomita, E. (eds) WALCOM: Algorithms and Computation. WALCOM 2015. Lecture Notes in Computer Science, vol 8973. Springer, Cham. https://doi.org/10.1007/978-3-319-15612-5_28

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  • DOI: https://doi.org/10.1007/978-3-319-15612-5_28

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15611-8

  • Online ISBN: 978-3-319-15612-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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