Process modeling: Difference between revisions

Revision as of 15:03, 30 June 2016

Revision as of 20:10, 8 July 2016

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In particular, the framework is too static in its view upon semantic quality, mainly considering models, not modeling activities, and comparing these models to a static ___domain rather than seeing the model as a facilitator for changing the ___domain.

Also, the framework’s definition of pragmatic quality is quite narrow, focusing on understanding, in line with the semiotics of Morris, while newer research in linguistics and semiotics has focused beyond mere understanding, on how the model is used and impactaffects its interpreters.

The need for a more dynamic view in the semiotic quality framework is particularly evident when considering process models, which themselves often prescribe or even enact actions in the problem ___domain, hence a change to the model may also change the problem ___domain directly. This paper discusses the quality framework in relation to active process models and suggests a revised framework based on this.

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Most experiments carried out relate to the relationship between metrics and quality aspects and these works have been done individually by different authors: Canfora et al. study the connection mainly between count metrics (for example, the number of tasks or splits -and maintainability of software process models;<ref>{{cite journal |first=G. |last=Canfora |first2=F. |last2=Garcia |first3=M. |last3=Piattini |first4=F. |last4=Ruiz |first5=C. |last5=Visaggio |title=A family of experiments to validate metrics for software process models |journal=Journal of Systems and Software |volume=77 |issue=2 |year=2005 |pages=113–129 |doi=10.1016/j.jss.2004.11.007 }}</ref> Cardoso validates the correlation between control flow complexity and perceived complexity; and Mendling et al. use metrics to predict control flow errors such as deadlocks in process models.<ref name=MendlingMoserBPM/><ref>J. Mendling, Detection and prediction of errors in epc business process models, Ph.D. thesis, Vienna University of Economics and Business Administration, http://wi.wu-wien.ac.at/home/mendling/publications/Mendling%20Doctoral%20thesis.pdf, 2007.</ref>

The results reveal that an increase in size of a model appears to havereduce a negative impact onits quality and their comprehensibility.

Further work by Mendling et al. investigates the connection between metrics and understanding <ref name=mendling14/> and<ref>J. Mendling and M. Strembeck, Influence factors of understanding business process models. In: W. Abramowicz and D. Fensel, Editors, Proceedings of the 11th International Conference on Business Information Systems (BIS 2008), Lecture Notes in Business Information Processing vol. 7, Springer-Verlag (2008), p. 142153.</ref> While some metrics are confirmed regarding their impacteffect, also personal factors of the modeler – like competence – are revealed as important for understanding about the models.

Several empirical surveys carried out still do not give clear guidelines or ways of evaluating the quality of process models but it is necessary to have clear set of guidelines to guide modelers in this task. Pragmatic guidelines have been proposed by different practitioners even though it is difficult to provide an exhaustive account of such guidelines from practice.

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From the research.<ref>J. Mendling, H.A. Reijers, J. Recker, Activity Labeling in Process Modeling: Empirical Insights and Recommendations, Information Systems. URL: <http://eprints.qut.edu.au/19625/></ref> value of process models is not only dependent on the choice of graphical constructs but also on their annotation with textual labels which need to be analyzed. It was found that it results in better models in terms of understanding than alternative labelling styles.

From the earlier research and ways to evaluate process model quality it has been seen that the process model's size, structure, expertise of the modeler and modularity have an impact onaffect its overall understandabilitycomprehensibility.<ref name=mendling14>J. Mendling, H.A. Reijers and J. Cardoso, What makes process models understandable? In: G. Alonso, P. Dadam and M. Rosemann, Editors, Business Process Management, 5th International Conference, BPM 2007, Brisbane, Australia, September 24–28, 2007, Proceedings, Lecture Notes in Computer Science vol. 4714, Springer, Brisbane, Australia (2007), pp. 48–63.</ref>

<ref>H. A. Reijers, J. Mendling, Modularity in process models: Review and effects in: M. Dumas, M. Reichert, M.-C. Shan (Eds.), Business Process Management BPM 2008, Vol. 5240 of Lecture Notes in Computer Science, Springer, Milan, Italy, 2008, pp. 20-35</ref> Based on these a set of guidelines was presented<ref name=mendling19>J. Mendling, H. A. Reijers, W. M. P. van der Aalst, Seven process modeling guidelines (7pmg), QUT ePrints Report 12340, Queensland University of Technology (2008)</ref> 7 Process Modeling Guidelines (7PMG). This guideline uses the verb-object style, as well as guidelines on the number of elements in a model, the application of structured modeling, and the decomposition of a process model. The guidelines are as follows: