Enhancing ProMoEE and DyVProMo with Additional Features to Foster Empirical Studies in the Context of Process Models Comprehension

Ulm University

MA Abschlussvortrag, Florian Loth, Ort: Online, Datum: 29.03.2022, Zeit: 16:30 Uhr

Business Process Management (BPM) has become an important factor on management level for enterprises, as it offers the opportunity to increase productivity and lower cost. This has led to a wide use of BPM techniques in the industry,  offering the ability to describe processes, improve and automate them or respond to changes quickly. In order to visually represent processes, notations are used. One of the most common is Business Process Model and Notation (BPMN),  which is capable of displaying interconnected activities along with resources and other information. A process model that does not accurately represent the real world may lead to a reduction in above benefits. Therefore, enterprises have  an interest in skilled  experts creating high quality process models. In reality a lot of untrained personnel is involved in the modeling process. Hence, there is interest in efficient ways of helping novices to understand modeling languages.  That is why research on the comprehension of process models is being conducted. One area of research is the addition of constructs to the existing notation. In particular, the coloring of modeling elements can help to distinguish and  recognize them more easily. In this thesis two pre-existing applications dealing with the assistance of conducting research on modeling comprehension are fostered. One is an application to dynamically change the displayed model  elements to reduce complexity or providing help with model element names through the addition of annotations. It is fostered by expanding its functionality to dynamically add predefined colors to the model elements, providing another  way of supporting understanding. The other is a survey platform with the ability to create questionnaires including the functionality to view and edit process models. Hence, it aims at the conduction of empirical research on model comprehension. It is improved in its Maintainability, usability and Applicability. Moreover, the first application is fully integrated into the second one, providing the ability to use it for surveys in questionnaires.