Lamela Seijas, Pablo and Thompson, Simon and Taylor, Ramsay and Bogdanov, Kirill and Derrick, John (2014) Synapse: automatic behaviour inference and implementation comparison for Erlang. Technical report. University of Kent (Unpublished) (KAR id:42784)
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Abstract
In the open environment of the world wide web, it is natural that there will be multiple providers of services, and that these service provisions — both specifications and implementations — will evolve. This multiplicity gives the user of these services a set of questions about how to choose between different providers, as well as how these choices work in an evolving environment.
The challenge, therefore, is to concisely represent to the user the behaviour of a particular implementation, and the differences between this implementation and alternative versions. Inferred models of software behaviour – and automatically derived and graphically presented comparisons between them – serve to support effective decision making in situations where there are competing implementations of requirements.
In this paper we use state machine models as the abstract representation of the behaviour of an implementation, and using these we build a tool by which one can visualise in an intuitive manner both the initial implementation and the differences between alternative versions. In this paper we describe our tool Synapse which implements this functionality by means of our grammar inference tool StateChum and a model-differencing algorithm. We describe the main functionality of Synapse, and demonstrate its usage by comparing different implementations of an example program from the existing literature.
Item Type: | Reports and Papers (Technical report) |
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Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76 Computer software |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Pablo Lamela-Seijas |
Date Deposited: | 29 Aug 2014 17:45 UTC |
Last Modified: | 08 Dec 2022 14:42 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/42784 (The current URI for this page, for reference purposes) |
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