Mining branching-time scenarios

Dirk Fahland, David Lo, Shahar Maoz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Specification mining extracts candidate specification from existing systems, to be used for downstream tasks such as testing and verification. Specifically, we are interested in the extraction of behavior models from execution traces. In this paper we introduce mining of branching-time scenarios in the form of existential, conditional Live Sequence Charts, using a statistical data-mining algorithm. We show the power of branching scenarios to reveal alternative scenario-based behaviors, which could not be mined by previous approaches. The work contrasts and complements previous works on mining linear-time scenarios. An implementation and evaluation over execution trace sets recorded from several real-world applications shows the unique contribution of mining branching-time scenarios to the state-of-the-art in specification mining.

Original languageEnglish
Title of host publication2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings
Pages443-453
Number of pages11
DOIs
StatePublished - 2013
Event2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Palo Alto, CA, United States
Duration: 11 Nov 201315 Nov 2013

Publication series

Name2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings

Conference

Conference2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013
Country/TerritoryUnited States
CityPalo Alto, CA
Period11/11/1315/11/13

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