MINOS(IIS): infeasibility analysis using MINOS
Computers and Operations Research
The algorithmic analysis of hybrid systems
Theoretical Computer Science - Special issue on hybrid systems
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Journal of Computer and System Sciences
LICS '96 Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science
Electronic Notes in Theoretical Computer Science (ENTCS)
BACH: Bounded reachAbility CHecker for linear hybrid automata
Proceedings of the 2008 International Conference on Formal Methods in Computer-Aided Design
Verifying Industrial Hybrid Systems with MathSAT
Electronic Notes in Theoretical Computer Science (ENTCS)
Reachability for linear hybrid automata using iterative relaxation abstraction
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
BACH 2: Bounded reachAbility CHecker for compositional linear hybrid systems
Proceedings of the Conference on Design, Automation and Test in Europe
Path-oriented bounded reachability analysis of composed linear hybrid systems
International Journal on Software Tools for Technology Transfer (STTT)
PHAVer: algorithmic verification of hybrid systems past hytech
HSCC'05 Proceedings of the 8th international conference on Hybrid Systems: computation and control
S2PF: speculative symbolic PathFinder
ACM SIGSOFT Software Engineering Notes
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In the authors' previous work, we proposed a linear programming (LP) based approach to check the reachability specification along one abstract path in a linear hybrid automaton (LHA) at a time by translating the reachability problem into the satisfiability problem of a linear constraint set. Then a depth-first-search (DFS) is deployed on the graph structure of the LHA to check all the paths with length in the threshold to answer the question of bounded reachability. In this DFS-style bounded model checking (BMC) algorithm, once a path is found to be infeasible by the underlying LP solver, a backtracking on the graph structure will be conducted. Clearly, the efficiency of the algorithm depends on the accuracy of the backtracking. If the DFS can backtrack to the most reasonable location, the state space need to search and verify can be reduced significantly. Fortunately, once a linear constraint set is judged to be unsatisfiable, the irreducible infeasible set (IIS) technique can be deployed on the unsatisfiable constraint set to give a quick analysis and find a small set of constraints which makes the whole program unsatisfiable. In this paper, we adopt this technique into our DFS-style BMC of LHA to locate the nodes and transitions which make the path under verification infeasible to guide the backtracking and answer the bounded reachability of LHA more efficiently.