Symbolic Discord Computation for Efficient Analysis of Message Sequence Charts
Message sequence charts (MSCs) and high-level MSCs (HMSCs) have been standardized to model interactions of parallel processes as message exchanges. We can flexibly express parallel behaviors with MSCs, but alternatively, it is possible to put unintended orders of messages into the MSCs. This paper f...
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| Veröffentlicht in: | Information and Media Technologies 2011, Vol.6(4), pp.1116-1127 |
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| container_title | Information and Media Technologies |
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| creator | Kakiuchi, Yosuke Nakagawa, Tomofumi Hamaguchi, Kiyoharu Tanimoto, Tadaaki Nakanishi, Masaki |
| description | Message sequence charts (MSCs) and high-level MSCs (HMSCs) have been standardized to model interactions of parallel processes as message exchanges. We can flexibly express parallel behaviors with MSCs, but alternatively, it is possible to put unintended orders of messages into the MSCs. This paper focuses on detection of such unintended orders as discord. We propose an encoding scheme in which the analysis of an HMSC is converted into a boolean SAT problem. Experimental results show that our approach achieves efficient analysis of HMSCs which have a large number of processes or a large size of graphs. This contributes efficient analysis of specification on complex interactions. |
| doi_str_mv | 10.11185/imt.6.1116 |
| format | Article |
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| source | J-STAGE Free; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Boolean algebra Charts Computation Encoding Exchange Graphs Messages Specifications |
| title | Symbolic Discord Computation for Efficient Analysis of Message Sequence Charts |
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