Blogs (1) >>
ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Thu 14 Nov 2019 13:40 - 14:00 at Cortez 2&3 - Mining and Bug Detection Chair(s): Chanchal K. Roy

Precisely modeling complex systems like cyber-physical systems is challenging, which often render model-based system verification techniques like model checking infeasible. To overcome this challenge, we propose a method called LAR to automatically ‘verify’ such complex systems through a combination of learning, abstraction and refinement from a set of system log traces. We assume that log traces and sampling frequency are adequate to capture ‘enough’ behaviour of the system. Given a safety property and the concrete system log traces as input, LAR automatically learns and refines system models, and produces two kinds of outputs. One is a counterexample with a bounded probability of being spurious. The other is a probabilistic model based on which the given property is ‘verified’. The model can be viewed as a proof obligation, i.e., the property is verified if the model is correct. It can also be used for subsequent system analysis activities like runtime monitoring or model-based testing. Our method has been implemented as a self-contained software toolkit. The evaluation on multiple benchmark systems as well as a real-world water treatment system shows promising results.

Thu 14 Nov

13:40 - 15:20: Papers - Mining and Bug Detection at Cortez 2&3
Chair(s): Chanchal K. RoyUniversity of Saskatchewan
ase-2019-Journal-First-Presentations13:40 - 14:00
Automatically 'Verifying' Complex Systems through Learning, Abstraction and Refinement
Jingyi WangNational University of Singapore, Singapore, Jun SunSingapore Management University, Singapore, Shengchao QinUniversity of Teesside, Cyrille JegourelISTD, Singapore University of Technology and Design
Link to publication
ase-2019-Journal-First-Presentations14:00 - 14:20
Interactive semi-automated specification mining for debugging: An experience report
Mohammad Jafar MashhadiUniversity of Calgary, Taha R. SiddiquiInfoMagnetics Technologies Corp, Hadi HemmatiUniversity of Calgary, Howard W. LoewenDepartment of Electrical & Computer Engineering, University of Calgary
Link to publication
ase-2019-Journal-First-Presentations14:20 - 14:40
Improving reusability of software libraries through usage pattern mining
Mohamed Aymen SaiedConcordia University, Ali OuniETS Montreal, University of Quebec, Houari SahraouiUniversité de Montréal, Raula Gaikovina KulaNAIST, Katsuro InoueOsaka University, David LoSingapore Management University
Link to publication
ase-2019-Journal-First-Presentations14:40 - 15:00
Rule-based specification mining leveraging learning to rank
Zherui CaoZhejiang University, Yuan TianQueens University, Kingston, Canada, Tien-Duy B. LeSchool of Information Systems, Singapore Management University, David LoSingapore Management University
Link to publication
ase-2019-Demonstrations15:00 - 15:10
TsmartGP: A Tool for Finding Memory Defects with Pointer Analysis
Yuexing WangTsinghua University, Guang ChenTsinghua University, Min ZhouTsinghua University, Ming GuTsinghua University, Jiaguang SunTsinghua University
ase-2019-Demonstrations15:10 - 15:20
Ares: Inferring Error Specifications through Static Analysis
Li ChiTsinghua University, Zuxing GuSchool of Software, Tsinghua University, Min ZhouTsinghua University, Ming GuTsinghua University, Hongyu ZhangThe University of Newcastle