Managing Variability in Process-Aware Information Systems

Relatore
Marcello La Rosa - Faculty of Information Technology, Queensland University of Technology

Data e ora
lunedì 12 gennaio 2009 alle ore 16.15 - Ore 16.15 caffe' e pasticcini - ore 16.30 inizio seminario

Luogo
Ca' Vignal 3 - Piramide, Piano 0, Sala Verde

Referente
Carlo Combi

Referente esterno

Data pubblicazione
22 dicembre 2008

Dipartimento
 

Riassunto

Configurable process models are integrated representations of multiple variants of a
process model in a given domain, e.g.\ multiple variants of a shipment-to-delivery
process in the logistics domain. Configurable process models provide a basis for
managing variability and for enabling reuse of process models in Process-Aware
Information Systems. Rather than designing process models from scratch, analysts can
derive process models by configuring existing ones, thereby reusing proven practices.
 
This presentation starts with the observation that existing approaches for managing
configurable process models suffer from two shortcomings that affect their usability in
practice. Firstly, configuration is performed manually and as such it is error-prone. In
particular, analysts are left with the burden of ensuring the correctness of the
individualized models. Secondly, existing approaches suffer from a lack of decision
support for the selection of configuration alternatives. Consequently, stakeholders
involved in the process model configuration need to possess expertise both in the
application domain and in the modeling language employed. This assumption represents an
adoption obstacle in domains where users are unfamiliar with modeling notations.
 
This presentation exposes an integrated framework to manage the configuration of process
models that aims to address the above shortcomings. The framework is grounded on two
interrelated contributions: (i) a conceptual foundation for correctness-preserving
configuration of process models, and (ii) a questionnaire-driven approach for process
model configuration, providing decision support and abstraction from modeling notations.
While the framework is language-independent, an embodiment of this framework in the
context of a process modeling language used in practice is also discussed.

 

 

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