TY - GEN
T1 - Vacuity aware falsification for MTL request-response specifications
AU - Dokhanchi, Adel
AU - Yaghoubi, Shakiba
AU - Hoxha, Bardh
AU - Fainekos, Georgios
N1 - Funding Information:
∗The authors are with the School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, U.S.A. Email: {adokhanc,syaghoub,fainekos}@asu.edu †The author is with the Department of Computer Science, Southern Illinois University, Carbondale, IL, U.S.A. Email: bhoxha@cs.siu.edu This research was partially funded by NSF awards CNS-1350420, CNS-1319560 and IIP-1361926, and the NSF I/UCRC Center for Embedded Systems.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - We propose a method to improve the automated test case generation for Metric Temporal Logic (MTL) falsification for Cyber-Physical Systems (CPS). In this work, we focus on request-response MTL specifications. That is, specifications that consist of at least one antecedent and a corresponding consequent. Test case generation is particularly difficult for these specifications since the consequent is only considered if the antecedent is satisfied. Therefore, we propose a method that first targets the antecedent in the specification. We show that our framework can improve upon existing falsification methods on a number of benchmark problems.
AB - We propose a method to improve the automated test case generation for Metric Temporal Logic (MTL) falsification for Cyber-Physical Systems (CPS). In this work, we focus on request-response MTL specifications. That is, specifications that consist of at least one antecedent and a corresponding consequent. Test case generation is particularly difficult for these specifications since the consequent is only considered if the antecedent is satisfied. Therefore, we propose a method that first targets the antecedent in the specification. We show that our framework can improve upon existing falsification methods on a number of benchmark problems.
UR - http://www.scopus.com/inward/record.url?scp=85044963940&partnerID=8YFLogxK
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U2 - 10.1109/COASE.2017.8256286
DO - 10.1109/COASE.2017.8256286
M3 - Conference contribution
AN - SCOPUS:85044963940
T3 - IEEE International Conference on Automation Science and Engineering
SP - 1332
EP - 1337
BT - 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017
PB - IEEE Computer Society
T2 - 13th IEEE Conference on Automation Science and Engineering, CASE 2017
Y2 - 20 August 2017 through 23 August 2017
ER -