Statistical Model Checking of Web Services

Research output: ThesisDoctoral ThesisThesis 4: defended at external organisation, OU (co-)supervisor, external graduate


In recent years, the increasing interest on service-oriented paradigm has given rise to a series of supporting tools and languages. In particular, COWS (Calculus for Orchestration of Web Services) has been attracting the attention of part of the scientific community for its peculiar
effort in formalising the semantics of the de facto standard Web Services orchestration language WS-BPEL. The purpose of the present work is to provide the tools for representing and evaluating the performance of Web Services modelled through COWS. In order to do this, a stochastic version of COWS is proposed: such a language allows us to describe the performance of the modelled systems and thus to represent Web Services both from the qualitative and quantitative points of view. In particular, we provide COWS with an extension which maintains the polyadic matching mechanism: this way, the language will still provide the capability to explicitly model the use of session identifiers. The resulting Scows is then equipped with a software tool which allows us to effectively perform model checking without incurring into the problem of statespace explosion, which would otherwise thwart the computation efforts even when checking relatively small models. In order to obtain this result, the proposed tool relies on the statistical analysis of simulation traces, which allows us to deal with large state-spaces without the actual need to completely explore them. Such an improvement in model checking performances comes at the price of accuracy in the answers provided: for this reason, users can trade-off speed against accuracy by modifying a series of parameters. In order to assess the efficiency of the proposed technique, our tool is compared with a number of existing model checking softwares.
Original languageEnglish
Awarding Institution
  • University of Trento
  • Quaglia, Paola, Supervisor, External person
Award date5 Mar 2010
Publication statusPublished - 2010
Externally publishedYes


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