Understanding Declare Models: Strategies, Pitfalls, Empirical Results

Haisjackl, Cornelia and Barba, Irene and Zugal, Stefan and Soffer, Pnina and Hadar, Irit and Reichert, Manfred and Pinggera, Jakob and Weber, Barbara (2016) Understanding Declare Models: Strategies, Pitfalls, Empirical Results. Software & Systems Modeling, 15 (2). pp. 325-352. ISSN 1619-1374

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Abstract

Declarative approaches to business process modeling are regarded as well suited for highly volatile environments, as they enable a high degree of flexibility. However, problems in understanding and maintaining declarative process models often impede their adoption. Likewise, little research has been conducted into the understanding of declarative process models. This paper takes a first step
toward addressing this fundamental question and reports on an empirical investigation consisting of an exploratory study and a follow-up study focusing on the system analysts'
sense-making of declarative process models that are specified in Declare. For this purpose, we distributed real-world Declare models to the participating subjects and asked them to describe the illustrated process and to perform a series of sense-making tasks. The results of our studies indicate that two main strategies for reading Declare models exist: either considering the execution order of the activities in the process model, or orienting by the layout of the process model. In addition, the results indicate that single constraints can be handled well by most subjects, while combinations of constraints pose significant challenges. Moreover, the study revealed that aspects that are similar in both imperative and declarative process modeling languages at a graphical level,
while having different semantics, cause considerable troubles. This research not only helps guiding the future development of tools for supporting system analysts,but also gives advice on the design of declarative process modeling notations and points out typical pitfalls to teachers and educators of future systems analysts.

Item Type: Article
Subjects: DBIS Research > Publications
Depositing User: Prof. Dr. Manfred Reichert
Date Deposited: 02 Oct 2014 16:12
Last Modified: 24 Apr 2016 12:08
URI: http://dbis.eprints.uni-ulm.de/id/eprint/1090

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