An Abstract Framework for Deadlock Prevention in BIP

Part 6: Session 5: Model CheckingInternational audienceWe present a sound but incomplete criterion for checking deadlock freedom of finite state systems expressed in BIP: a component-based framework for the construction of complex distributed systems. Since deciding deadlock-freedom for finite-state concurrent systems is PSPACE-complete, our criterion gives up completeness in return for tractability of evaluation. Our criterion can be evaluated by model-checking subsystems of the overall large system. The size of these subsystems depends only on the local topology of direct interaction between components, and not on the number of components in the overall system. We present two experiments, in which our method compares favorably with existing approaches. For example, in verifying deadlock freedom of dining philosphers, our method shows linear increase in computation time with the number of philosophers, whereas other methods (even those that use abstraction) show super-linear increase, due to state-explosion

Data and abstraction for scenario-based modeling with Petri nets

Scenario-based modeling is an approach for describing behaviors of a distributed system in terms of partial runs, called scenarios. Deriving an operational system from a set of scenarios is the main challenge that is typically addressed by either synthesizing system components or by providing operational semantics. Over the last years, several established scenario-based techniques have been adopted to Petri nets. Their adaptation allows for verifying scenario-based models and for synthesizing individual components from scenarios within one formal technique, by building on Petri net theory. However, current adaptations of scenarios face two limitations: a system modeler (1) cannot abstract from concrete behavior, and (2) cannot explicitly describe data in scenarios. This paper lifts these limitations for scenarios in the style of Live Sequence Charts (LSCs). We extend an existing model for scenarios, that features Petri net-based semantics, verification and synthesis techniques, and close the gap between LSCs and Petri nets further

To compose, or not to compose, that is the question:an analysis of compositional state space generation

\u3cp\u3eTo combat state space explosion several compositional verification approaches have been proposed. One such approach is compositional aggregation, where a given system consisting of a number of parallel components is iteratively composed and minimised. Compositional aggregation has shown to perform better (in the size of the largest state space in memory at one time) than classical monolithic composition in a number of cases. However, there are also cases in which compositional aggregation performs much worse. It is unclear when one should apply compositional aggregation in favor of other techniques and how it is affected by action hiding and the scale of the model. This paper presents a descriptive analysis following the quantitiative experimental approach. The experiments were conducted in a controlled test bed setup in a computer laboratory environment. A total of eight scalable models with different network topologies considering a number of varying properties were investigated comprising 119 subjects. This makes it the most comprehensive study done so far on the topic. We investigate whether there is any systematic difference in the success of compositional aggregation based on the model, scaling, and action hiding. Our results indicate that both scaling up the model and hiding more behaviour has a positive influence on compositional aggregation.\u3c/p\u3