Learning Assumptions for Compositional Verification

@inproceedings{Cobleigh2003LearningAF,
  title={Learning Assumptions for Compositional Verification},
  author={Jamieson M. Cobleigh and D. Giannakopoulou and C. Pasareanu},
  booktitle={TACAS},
  year={2003}
}
Compositional verification is a promising approach to addressing the state explosion problem associated with model checking. One compositional technique advocates proving properties of a system by checking properties of its components in an assume-guarantee style. However, the application of this technique is difficult because it involves non-trivial human input. This paper presents a novel framework for performing assume-guarantee reasoning in an incremental and fully automated fashion. To… Expand
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References

SHOWING 1-10 OF 41 REFERENCES
Model checking and modular verification
Assumption generation for software component verification
You Assume, We Guarantee: Methodology and Case Studies
Compositional model checking
Checking safety properties using compositional reachability analysis
The rely-guarantee method for verifying shared variable concurrent programs
Context constraints for compositional reachability analysis
Adaptive Model Checking
Interface automata
Model Checking Programs
...
1
2
3
4
5
...