Please use this identifier to cite or link to this item: https://doi.org/10.1145/1985793.1985807
DC FieldValue
dc.titleMining message sequence graphs
dc.contributor.authorKumar, S.
dc.contributor.authorKhoo, S.-C.
dc.contributor.authorRoychoudhury, A.
dc.contributor.authorLo, D.
dc.date.accessioned2013-07-04T08:13:10Z
dc.date.available2013-07-04T08:13:10Z
dc.date.issued2011
dc.identifier.citationKumar, S.,Khoo, S.-C.,Roychoudhury, A.,Lo, D. (2011). Mining message sequence graphs. Proceedings - International Conference on Software Engineering : 91-100. ScholarBank@NUS Repository. <a href="https://doi.org/10.1145/1985793.1985807" target="_blank">https://doi.org/10.1145/1985793.1985807</a>
dc.identifier.isbn9781450304450
dc.identifier.issn02705257
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40823
dc.description.abstractDynamic specification mining involves discovering software behavior from traces for the purpose of program comprehension and bug detection. However, mining program behavior from execution traces is difficult for concurrent/distributed programs. Specifically, the inherent partial order relationships among events occurring across processes pose a big challenge to specification mining. In this paper, we propose a framework for mining partial orders so as to understand concurrent program behavior. Our miner takes in a set of concurrent program traces, and produces a message sequence graph (MSG) to represent the concurrent program behavior. An MSG represents a graph where the nodes of the graph are partial orders, represented as Message Sequence Charts. Mining an MSG allows us to understand concurrent program behaviors since the nodes of the MSG depict important "phases" or "interaction snippets" involving several concurrently executing processes. To demonstrate the power of this technique, we conducted experiments on mining behaviors of several fairly complex distributed systems. We show that our miner can produce the corresponding MSGs with both high precision and recall. © 2011 ACM.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1145/1985793.1985807
dc.sourceScopus
dc.subjectdistributed systems
dc.subjectspecification mining
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1145/1985793.1985807
dc.description.sourcetitleProceedings - International Conference on Software Engineering
dc.description.page91-100
dc.description.codenPCSED
dc.identifier.isiutNOT_IN_WOS
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