Abstract
We introduce loose graph simulations (LGS), a new notion about labelled graphs which subsumes in an intuitive and natural way subgraph isomorphism (SGI), regular language pattern matching (RLPM) and graph simulation (GS). Being a unification of all these notions, LGS allows us to express directly also problems which are “mixed” instances of previous ones, and hence which would not fit easily in any of them. After the definition and some examples, we show that the problem of finding loose graph simulations is NP-complete, we provide formal translation of SGI, RLPM, and GS into LGSs, and we give the representation of a problem which extends both SGI and RLPM. Finally, we identify a subclass of the LGS problem that is polynomial.
M. Miculan—Partially supported by PRID 2017 ENCASE of the University of Udine.
M. Peressotti—Partially supported by the Open Data Framework project at the University of Southern Denmark, and by the Independent Research Fund Denmark, Natural Sciences, grant no. DFF-7014-00041.
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Acknowledgements
We thank the anonymous reviewers and the participants to the GCM’17 workshop for their comments. We thank Andrea Corradini for his insightful observations on a preliminary version of this work and for proposing the name “loose graph simulations”.
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Mansutti, A., Miculan, M., Peressotti, M. (2018). Loose Graph Simulations. In: Seidl, M., Zschaler, S. (eds) Software Technologies: Applications and Foundations. STAF 2017. Lecture Notes in Computer Science(), vol 10748. Springer, Cham. https://doi.org/10.1007/978-3-319-74730-9_9
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DOI: https://doi.org/10.1007/978-3-319-74730-9_9
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