TY - GEN
T1 - Discriminative model checking
AU - Niebert, Peter
AU - Peled, Doron
AU - Pnueli, Amir
PY - 2008
Y1 - 2008
N2 - Model checking typically compares a system description with a formal specification, and returns either a counterexample or an affirmation of compatibility between the two descriptions. Counterexamples provide evidence to the existence of an error, but it can still be very difficult to understand what is the cause for that error. We propose a model checking methodology which uses two levels of specification. Under this methodology, we group executions as good and bad with respect to satisfying a base LTL specification. We use an analysis specification, in CTL* style, quantifying over the good and bad executions. This specification allows checking not only whether the base specification holds or fails to hold in a system, but also how it does so. We propose a model checking algorithm in the style of the standard CTL* decision procedure. This framework can be used for comparing between good and bad executions in a system and outside it, providing assistance in locating the design or programming errors.
AB - Model checking typically compares a system description with a formal specification, and returns either a counterexample or an affirmation of compatibility between the two descriptions. Counterexamples provide evidence to the existence of an error, but it can still be very difficult to understand what is the cause for that error. We propose a model checking methodology which uses two levels of specification. Under this methodology, we group executions as good and bad with respect to satisfying a base LTL specification. We use an analysis specification, in CTL* style, quantifying over the good and bad executions. This specification allows checking not only whether the base specification holds or fails to hold in a system, but also how it does so. We propose a model checking algorithm in the style of the standard CTL* decision procedure. This framework can be used for comparing between good and bad executions in a system and outside it, providing assistance in locating the design or programming errors.
UR - http://www.scopus.com/inward/record.url?scp=48949089490&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-70545-1_48
DO - 10.1007/978-3-540-70545-1_48
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AN - SCOPUS:48949089490
SN - 3540705430
SN - 9783540705437
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 504
EP - 516
BT - Computer Aided Verification - 20th International Conference, CAV 2008, Proceedings
T2 - 20th International Conference on Computer Aided Verification, CAV 2008
Y2 - 7 July 2008 through 14 July 2008
ER -