Epidemic Analysis Using Traditional Model Checking and Stochastic Simulation

Stochastic model checking has been the mainstay for formal analysis of epidemic progression in recent years. However, such methods are sensitive to inaccuracies in estimating stochastic parameters like infection transmission and recovery rates. In this work, we revert to traditional model checking (specifically, for timed automata) to absorb inaccurately provided parameters into the non-determinism inherent in such traditional formalisms. Parameters obtained through stochastic simulation are used by the timed automata, with suficiently wide windows of non-determinism to account for error. A positive side effect of this approach is that separating the probabilistic component from actual epidemic timed automata model, helps us to focus on the progression logic while building the model

On Memory-Block Traversal Problems in Model-Checking Timed Systems

. A major problem in model-checking timed systems is the huge memory requirment. In this paper, we study the memory-block traversal problems of using standard operating systems in exploring the state-space of timed automata. We report a case study which demonstrates that deallocating memory blocks (i.e. memory-block traversal) using standard memory management routines is extremely time-consuming. The phenomenon is demonstrated in a number of experiments by installing the Uppaal tool on Windows95, SunOS 5 and Linux. It seems that the problem should be solved by implementing a memory manager for the model-checker, which is a troublesome task as it is involved in the underlining hardware and operating system. We present an alternative technique that allows the model-checker to control the memory-block traversal strategies of the operating systems without implementing an independent memory manager. The technique is implemented in the Uppaal model-checker. Our experiments demonstr..