Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

1-2016

Abstract

Software systems are often developed and released without formal specifications. For those systems that are formally specified, developers have to continuously maintain and update the specifications or have them fall out of date. To deal with the absence of formal specifications, researchers have proposed techniques to infer the missing specifications of an implementation in a variety of forms, such as finite state automaton (FSA). Despite the progress in this area, the efficacy of the proposed specification miners needs to improve if these miners are to be adopted. We propose SpecForge, a new specification mining approach that synergizes many existing specification miners. SpecForge decomposes FSAs that are inferred by existing miners into simple constraints, through a process we refer to as model fission. It then filters the outlier constraints and fuses the constraints back together into a single FSA (i.e., model fusion). We have evaluated SpecForge on execution traces of 10 programs, which includes 5 programs from DaCapo benchmark, to infer behavioral models of 13 library classes. Our results show that SpecForge achieves an average precision, recall and F-measure of 90.57%, 54.58%, and 64.21% respectively. SpecForge outperforms the best performing baseline by 13.75% in terms of F-measure.

Keywords

Model Fission, Model Fusion, Specification Mining, Synergizing Miners

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

30th IEEE/ACM International Conference on Automated Software Engineering (ASE 2015)

First Page

115

Last Page

125

ISBN

9781509000241

Identifier

10.1109/ASE.2015.83

City or Country

Lincoln, USA

Additional URL

http://doi.org/10.1109/ASE.2015.83

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