Approximate Model Checking Verification Real-Time System Linear Duration Invariant Genetic Algorithm
Issue Date:
2013
Publisher:
Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Citation:
Serdica Journal of Computing, Vol. 7, No 1, (2013), 1p-12p
Abstract:
Real-time systems are usually modelled with timed automata and real-time requirements relating to the state durations of the system are
often specifiable using Linear Duration Invariants, which is a decidable subclass of Duration Calculus formulas. Various algorithms have been developed
to check timed automata or real-time automata for linear duration invariants, but each needs complicated preprocessing and exponential calculation.
To the best of our knowledge, these algorithms have not been implemented. In this paper, we present an approximate model checking technique based
on a genetic algorithm to check real-time automata for linear durration invariants in reasonable times. Genetic algorithm is a good optimization
method when a problem needs massive computation and it works particularly well in our case because the fitness function which is derived from the
linear duration invariant is linear. ACM Computing Classification System (1998): D.2.4, C.3.
