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THE COMPLEXITY OF COVERAGE

    https://doi.org/10.1142/S0129054113400066Cited by:1 (Source: Crossref)

    We study the problem of generating a test sequence that achieves maximal coverage for a reactive system under test. We formulate the problem as a repeated game between the tester and the system, where the system state space is partitioned according to some coverage criterion and the objective of the tester is to maximize the set of partitions (or coverage goals) visited during the game. We show the complexity of the maximal coverage problem for non-deterministic systems is PSPACE-complete, but is NP-complete for deterministic systems. For the special case of non-deterministic systems with a re-initializing “reset” action, which represent running a new test input on a re-initialized system, we show that the complexity is coNP-complete. Our proof technique for reset games uses randomized testing strategies that circumvent the exponentially large memory requirement of deterministic testing strategies. We also discuss the memory requirement for deterministic strategies and extensions of our results to other models, such as pushdown systems and timed systems.

    This research was funded in part by the US NSF grants CCR-0132780 and CNS-0720884, CCF-0546170, CNS-0702881, DARPA grant HR0011-09-1-0037, Austrian Science Fund (FWF) NFN Grant S11407-N23 (RiSE), ERC Start Grant (279307: Graph Games) and a Microsoft faculty fellowship.

    A preliminary version of the paper appeared in APLAS 2008.