Using integer programming to verify general safety and liveness properties
Formal Methods in System Design - Special issue on computer-aided verification (based on CAV'92 workshop)
Coverage estimation for symbolic model checking
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Symbolic model checking using SAT procedures instead of BDDs
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Symbolic Model Checking
Coverage Metrics for Temporal Logic Model Checking
TACAS 2001 Proceedings of the 7th International Conference on Tools and Algorithms for the Construction and Analysis of Systems
VIS: A System for Verification and Synthesis
CAV '96 Proceedings of the 8th International Conference on Computer Aided Verification
Symbolic Model Checking of Infinite State Systems Using Presburger Arithmetic
CAV '97 Proceedings of the 9th International Conference on Computer Aided Verification
RTL-Datapath Verification using Integer Linear Programming
ASP-DAC '02 Proceedings of the 2002 Asia and South Pacific Design Automation Conference
Using Integer Equations for High Level Formal Verification Property Checking
ISQED '03 Proceedings of the 4th International Symposium on Quality Electronic Design
Proceedings of the conference on Design, automation and test in Europe
Optimization of data-flow computations using canonical TED representation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Optimizing data flow graphs to minimize hardware implementation
Proceedings of the Conference on Design, Automation and Test in Europe
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This paper proposes a word-level coverage metric to determine the completeness of a set of properties verified by a word-level method. An algorithm is presented to compute a functionality based coverage metric for a sequence property as specification. Control, intermediate and output signals are represented by a multiplexer based structure of linear integer equations, and RT level properties are directly applied to this representation. A set of integer equations are symbolically simulated based on the specified property in a predictable time. We used a canonical form of linear Taylor Expansion Diagram.