Abstract
The growing availability of distributed and cloud computing frameworks makes it possible to face complex computational problems in a more effective and convenient way. A notable example is state-space exploration of discrete-event systems specified in a formal way. The exponential complexity of this task is a major limitation to the usage of consolidated analysis techniques and tools. Several techniques for addressing the state space explosion problem within this context have been studied in the literature. One of these is to use distributed memory and computation to deal with the state space explosion problem. In this paper we study and compare two different approaches, relying on distributed and cloud frameworks, respectively. These approaches were designed and implemented following the same computational schema, a sort of map & fold. They are applied on symbolic state-space exploration of real-time systems specified by (a timed extension of) Petri Nets, by re-adapting a sequential algorithm implemented as a command-line Java tool. The outcome of several tests performed on a benchmarking specification are presented, thus showing the convenience of distributed approaches.