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2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) (2017)
Urbana, IL, USA
Oct. 30, 2017 to Nov. 3, 2017
ISBN: 978-1-5386-3976-4
pp: 901-906
Lukas Schmidt , Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Apurva Narayan , Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Sebastian Fischmeister , Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
ABSTRACT
Software specifications are useful for software validation, model checking, runtime verification, debugging, monitoring, etc. In context of safety-critical real-time systems, temporal properties play an important role. However, temporal properties are rarely present due to the complexity and evolutionary nature of software systems. We propose Timed Regular Expression Mining (TREM) a hosted tool for specification mining using timed regular expressions (TREs). It is designed for easy and robust mining of dominant temporal properties. TREM uses an abstract structure of the property; the framework constructs a finite state machine to serve as an acceptor. TREM is scalable, easy to access/use, and platform independent specification mining framework. The tool is tested on industrial strength software system traces such as the QNX real-time operating system using traces with more than 1.5 Million entries. The tool demonstration video can be accessed here: youtu.be/cSd_aj3_LH8
INDEX TERMS
Data mining, Automata, Tools, Software, Debugging, Real-time systems, Monitoring
CITATION

L. Schmidt, A. Narayan and S. Fischmeister, "TREM: A tool for mining timed regular specifications from system traces," 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE), Urbana, IL, USA, 2017, pp. 901-906.
doi:10.1109/ASE.2017.8115702
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