Modelling and Validating a multiple-configuration railway signalling system using SDL

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Adding Sessions to BPEL

By considering an essential subset of the BPEL orchestration language, we define SeB, a session based style of this subset. We discuss the formal semantics of SeB and we present its main properties. We use a new approach to address the formal semantics, based on a translation into so-called control graphs. Our semantics handles control links and addresses the static semantics that prescribes the valid usage of variables. We also provide the semantics of collections of networked services. Relying on these semantics, we define precisely what is meant by interaction safety, paving the way to the formal analysis of safe interactions between BPEL services

Enhancing Test Coverage by Back-tracing Model-checker Counterexamples

AbstractThe automatic detection of unreachable coverage goals and generation of tests for "corner-case" scenarios is crucial to make testing and simulation based verification more effective. In this paper we address the problem of coverability analysis and test case generation in modular and component based systems. We propose a technique that, given an uncovered branch in a component, either establishes that the branch cannot be covered or produces a test case at the system level which covers the branch. The technique is based on the use of counterexamples returned by model checkers, and exploits compositionality to cope with large state spaces typical of real applications

Hacking an Ambiguity Detection Tool to Extract Variation Points: an Experience Report

Natural language (NL) requirements documents can be a precious source to identify variability information. This information can be later used to define feature models from which different systems can be instantiated. In this paper, we are interested in validating the approach we have recently proposed to extract variability issues from the ambiguity defects found in NL requirement documents. To this end, we single out ambiguities using an available NL analysis tool, QuARS, and we classify the ambiguities returned by the tool by distinguishing among false positives, real ambiguities, and variation points. We consider three medium sized requirement documents from different domains, namely, train control, social web, home automation. We report in this paper the results of the assessment. Although the validation set is not so large, the results obtained are quite uniform and permit to draw some interesting conclusions. Starting from the results obtained, we can foresee the tailoring of a NL analysis tool for extracting variability from NL requirement documents