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Title: Inferring Extended Finite State Machine Models from Software Executions
Authors: Walkinshaw, Neil
Taylor, R.
Derrick, J.
First Published: 2013
Presented at: 20th Working Conference on Reverse Engineering (WCRE 2013), Koblenz, Germany
Start Date: 14-Oct-2013
End Date: 17-Oct-2013
Abstract: The ability to reverse-engineer models of software behaviour is valuable for a wide range of software maintenance, validation and verification tasks. Current reverse-engineering techniques focus either on control-specific behaviour (e.g. in the form of Finite State Machines), or data-specific behaviour (e.g. as pre/post-conditions or invariants). However, typical software behaviour is usually a product of the two; models must combine both aspects to fully represent the software’s operation. Extended Finite State Machines (EFSMs) provide such a model. Although attempts have been made to infer EFSMs, these have been problematic. The models inferred by these techniques can be non deterministic, the inference algorithms can be inflexible, and only applicable to traces with specific characteristics. This paper presents a novel EFSM inference technique that addresses the problems of inflexibility and non determinism. It also adapts an experimental technique from the field of Machine Learning to evaluate EFSM inference techniques, and applies it to two open-source software projects.
DOI Link: 10.1109/WCRE.2013.6671305
Type: Conference Paper
Rights: Copyright © the authors, 2013.
Description: INSPEC Accession Number: 13916984
Appears in Collections:Conference Papers & Presentations, Dept. of Computer Science

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