Contradictory antecedent debugging in bounded model checking
Proceedings of the 19th ACM Great Lakes symposium on VLSI
The role of mutation analysis for property qualification
MEMOCODE'09 Proceedings of the 7th IEEE/ACM international conference on Formal Methods and Models for Codesign
On the notion of vacuous truth
LPAR'07 Proceedings of the 14th international conference on Logic for programming, artificial intelligence and reasoning
Property analysis and design understanding
Proceedings of the Conference on Design, Automation and Test in Europe
Strengthening properties using abstraction refinement
Proceedings of the Conference on Design, Automation and Test in Europe
Finding first-order minimal unsatisfiable cores with a heuristic depth-first-search algorithm
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
Towards a notion of unsatisfiable cores for LTL
FSEN'09 Proceedings of the Third IPM international conference on Fundamentals of Software Engineering
Propositional interpolation and abstract interpretation
ESOP'10 Proceedings of the 19th European conference on Programming Languages and Systems
Towards a notion of unsatisfiable and unrealizable cores for LTL
Science of Computer Programming
| Hi-index | 0.00 |
When model-checking reports that a property holds on a model, vacuity detection increases user confidence in this result by checking that the property is satisfied in the intended way. While vacuity detection is effective, it is a relatively expensive technique requiring many additional model-checking runs. We address the problem of efficient vacuity detection for Bounded Model Checking (BMC) of LTL properties, presenting three partial vacuity detection methods based on the efficient analysis of the resolution proof produced by a successful BMC run. In particular, we define a characteristic of resolution proofs - peripherality - and prove that if a variable is a source of vacuity, then there exists a resolution proof in which this variable is peripheral. Our vacuity detection tool, VaqTree, uses these methods to detect vacuous variables, decreasing the total number of model-checking runs required to detect all sources of vacuity.