An I/O Efficient Model Checking Algorithm for Large-Scale Systems


Model checking is a powerful approach for the formal verification of hardware and software systems. However, this approach suffers from the state space explosion problem, that limits its application to massive-scale systems due to house shortage. To overcome this drawback, one in all the foremost effective solutions is to use external memory algorithms. In this paper, we tend to propose an I/O economical model checking algorithm for massive-scale systems. To lower I/O complexity and improve time potency, we mix three new techniques: 1) a linear hash-sorting technique; a pair of) a cached duplicate detection technique; and 3) a dynamic path management technique. We tend to show that the new algorithm includes a lower I/O complexity than state-of-the-art I/O economical model checking algorithms, together with detect accepting cycle, maximal accepting predecessors, and iterative-deepening depth-initial search. Additionally, the experiments show that our algorithm obviously outperforms these three algorithms on the chosen representative benchmarks in terms of performance.

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