2013 20th Working Conference on Reverse Engineering (WCRE) (2013)
Koblenz, Germany Germany
Oct. 14, 2013 to Oct. 17, 2013
Neil Walkinshaw , Department of Computer Science, The University of Leicester, UK
Ramsay Taylor , Department of Computer Science, The University of Sheffield, UK
John Derrick , Department of Computer Science, The University of Sheffield, UK
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.
Inference algorithms, Automata, Software, Software algorithms, Merging, Data models, Machine learning algorithms
N. Walkinshaw, R. Taylor and J. Derrick, "Inferring Extended Finite State Machine models from software executions," 2013 20th Working Conference on Reverse Engineering (WCRE), Koblenz, Germany Germany, 2013, pp. 301-310.