Mining and Improving Composite Web Services Recovery Mechanisms

International audienceEnsuring composite services reliability is a challenging problem. Indeed, due to the inherent autonomy and heterogeneity of Web services it is difficult to predict and reason about the behavior of the overall composite service. Generally, previous approaches develop, using their modeling formalisms, a set of techniques to analyze the composition model and check “correctness” properties. Although powerful, these approaches may fail, in some cases, to ensure CS reliable executions even if they formally validate its composition model. This is because properties specified in the studied composition model remains assumptions that may not coincide with the reality (i.e. effective CS executions). Sharing the same issue, we present a reengineering approach that starts from CS executions log to improve its recovery mechanisms. Basically, we propose a set of mining techniques to discover CS transactional behavior from an event based log. Then, based on this mining step, we use a set of rules in order to improve its reliability

Discovering Workflow Patterns from Timed Logs

Traditionally, workflow modeling is typically done by interviews or questionnaires which stay quite limited for the acquisition of workflow models and their adaptation to changing requirements. In order to build such model, this paper proposes to “reverse the process”. The approach, we propose, is able to acquire workflow model from workflow log, which contains information about execution events. This paper presents a mining technique to discover workflows patterns (e.g. Sequence, Parallel split, Exclusive choice, etc.) from workflow event log in the objective to build a global workflow model. An event log is a view of a workflow execution at a given instant. The mining of workflow patterns is done by the combination of two complementary techniques: an algorithmic technique and a statistical analysis. The building of the global workflow model is done with bottom-up approach. The discovering technique proposed can deal with some ambiguities where the single use of an algorithmic technique method cannot resolve