Conference Proceeding Article
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that are formally specified, developers have to continuously maintain and update the specifications or have them fall out of date.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.
Model Fission, Model Fusion, Specification Mining, Synergizing Miners
Software and Cyber-Physical Systems
30th IEEE/ACM International Conference on Automated Software Engineering (ASE 2015)
City or Country
LE BUI TIEN DUY; LE DINH XUAN BACH; David LO; and BESCHASTNIKH, Ivan.
Synergizing specification miners through model fissions and fusions. (2016). 30th IEEE/ACM International Conference on Automated Software Engineering (ASE 2015). 115-125. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3084
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