Semantics of Higraphs for Process Modeling and Analysis

Elena Kushnareva (1) , Irina Rychkova (1) , Bénédicte Le Grand (1)

1 CRI - Centre de Recherche en Informatique de Paris 1

Knowledge and experience of a case manager remains a key success factor for Case Management Processes (CMPs). When a number of influential parameters is high, a number of possible scenarios grows significantly. Automated guidance in scenario evaluation and activity planning would be of a great help. In our previous work, we defined the statecharts semantics for visualisation and simulation of CMP scenarios. In this work, we formalise the state-oriented models with higraphs: higraphs provide mathematical foundation for statecharts and eventually enable a wide panoply of algorithms for process analysis and optimisation. We show how a statecharts diagram can be transformed into higraph and analysed at run-time with graph algorithms. In particular, we take an example of the Shortest Path algorithm and show how this algorithm can be used in order to guide the case manager suggesting her the best process scenario. Compared to BPM approaches, a state-oriented process scenario does not specify concrete activities but only the objectives and constraints to be met. Thus, our approach does not prescribe but describe an activity to be executed next. The manager can define an activity that fit the description " on the fly " , based on her experience and intuition.

Mots clés: Statecharts; Higraphs; process analysis

Domaines: Théorie et langage formel [cs.FL]

Elena Kushnareva, Irina Rychkova, Bénédicte Le Grand. Semantics of Higraphs for Process Modeling and Analysis. AdaptiveCM 2016 – 5th International Workshop on Adaptive Case Management and other non-workflow approaches to BPM, Sept. 2016, Vienna, Austria. , Sep 2016, Vienna, Austria. ⟨hal-01366350⟩