Towards Succinctness in Mining Scenario-Based Specifications
Specification mining methods are used to extract candidate specifications from system execution traces. A major challenge for specification mining is succinctness. That is, in addition to the soundness, completeness, and scalable performance of the specification mining method, one is interested in p...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2011
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/1400 http://dx.doi.org/10.1109/ICECCS.2011.30 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Specification mining methods are used to extract candidate specifications from system execution traces. A major challenge for specification mining is succinctness. That is, in addition to the soundness, completeness, and scalable performance of the specification mining method, one is interested in producing a succinct result, which conveys a lot of information about the system under investigation but uses a short, machine and human-readable representation. In this paper we address the succinctness challenge in the context of scenario-based specification mining, whose target formalism is live sequence charts (LSC), an expressive extension of classical sequence diagrams. We do this by adapting three classical notions: a definition of an equivalence relation over LSCs, a definition of a redundancy and inclusion relation based on isomorphic embeddings among LSCs, and a delta-discriminative measure based on an information gain metric on a sorted set of LSCs. These are applied on top of the commonly used statistical metrics of support and confidence. A number of case studies show the utility of our approach towards succinct mined specifications. |
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