4- https://doi.org/10.4204/eptcs.129.13
Abstraction and Learning for Infinite-State Compositional Verification
- Sep 19, 2013
- Electronic Proceedings in Theoretical Computer Science
- Dimitra Giannakopoulou +1 more
Despite many advances that enable the application of model checking techniques to the verification of large systems, the state-explosion problem remains the main challenge for scalability. Compositional verification addresses this challenge by decomposing the verification of a large system into the verification of its components. Recent techniques use learning-based approaches to automate compositional verification based on the assume-guarantee style reasoning. However, these techniques are only applicable to finite-state systems. In this work, we propose a new framework that interleaves abstraction and learning to perform automated compositional verification of infinite-state systems. We also discuss the role of learning and abstraction in the related context of interface generation for infinite-state components.
- # Compositional Verification
- # Verification Of Systems
- # Assume-guarantee Style
- # Model Checking Techniques
- # Challenge For Scalability
- # Infinite-state Systems
- # Finite-state Systems
- # Checking Techniques
- # Interface Generation
- # State-explosion Problem
