Communicating sequential processes
Communicating sequential processes
Symbolic model checking: 1020 states and beyond
Information and Computation - Special issue: Selections from 1990 IEEE symposium on logic in computer science
Model checking large software specifications
SIGSOFT '96 Proceedings of the 4th ACM SIGSOFT symposium on Foundations of software engineering
High performance BDD package by exploiting memory hierarchy
DAC '96 Proceedings of the 33rd annual Design Automation Conference
NuSMV 2: An OpenSource Tool for Symbolic Model Checking
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Automatic symbolic compositional verification by learning assumptions
Formal Methods in System Design
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
PAT: Towards Flexible Verification under Fairness
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
Model checking hierarchical probabilistic systems
ICFEM'10 Proceedings of the 12th international conference on Formal engineering methods and software engineering
JTLV: a framework for developing verification algorithms
CAV'10 Proceedings of the 22nd international conference on Computer Aided Verification
Build your own model checker in one month
Proceedings of the 2013 International Conference on Software Engineering
| Hi-index | 0.00 |
BDD-based symbolic model checking is capable of verifying systems with a large number of states. In this work, we report an extensible framework to facilitate symbolic encoding and checking of hierarchical systems. Firstly, a novel library of symbolic encoding functions for compositional operators (e.g., parallel composition, sequential composition, choice operator, etc.) are developed so that users can apply symbolic model checking techniques to hierarchical systems with little knowledge of symbolic encoding techniques (like BDD or CUDD). Secondly, as the library is language-independent, we build an extensible framework with various symbolic model checking algorithms so that the library can be easily applied to encode and verify different modeling languages. Lastly, the applicability and scalability of our framework are demonstrated by applying the framework in the development of symbolic model checkers for three modeling languages as well as a comparison with the NuSMV model checker.