A Short Survey on Process Model Similarity <s> The Challenge of Process Model Similarity <s> This paper discusses three specific challenges for process model reuse. Models are intrinsically biased towards a particular purpose. For reuse this bias needs to be neutralized. We focus on research that can ultimately contribute to a canonical representation of behavior, a canonical formulation of labels, and canonical terminology. Each of these three challenges is sketched and pointers to technical papers are provided. <s> BIB001 </s> A Short Survey on Process Model Similarity <s> The Challenge of Process Model Similarity <s> Large corporations increasingly utilize business process models for documenting and redesigning their operations. The extent of such modeling initiatives with several hundred models and dozens of often hardly trained modelers calls for automated quality assurance. While formal properties of control flow can easily be checked by existing tools, there is a notable gap for checking the quality of the textual content of models, in particular, its activity labels. In this paper, we address the problem of activity label quality in business process models. We designed a technique for the recognition of labeling styles, and the automatic refactoring of labels with quality issues. More specifically, we developed a parsing algorithm that is able to deal with the shortness of activity labels, which integrates natural language tools like WordNet and the Stanford Parser. Using three business process model collections from practice with differing labeling style distributions, we demonstrate the applicability of our technique. In comparison to a straightforward application of standard natural language tools, our technique provides much more stable results. As an outcome, the technique shifts the boundary of process model quality issues that can be checked automatically from syntactic to semantic aspects. <s> BIB002 </s> A Short Survey on Process Model Similarity <s> The Challenge of Process Model Similarity <s> This article studies the problem of transforming a process model with an arbitrary topology into an equivalent well-structured process model. While this problem has received significant attention, there is still no full characterization of the class of unstructured process models that can be transformed into well-structured ones, nor an automated method for structuring any process model that belongs to this class. This article fills this gap in the context of acyclic process models. The article defines a necessary and sufficient condition for an unstructured acyclic process model to have an equivalent well-structured process model under fully concurrent bisimulation, as well as a complete structuring method. The method has been implemented as a tool that takes process models captured in the BPMN and EPC notations as input. The article also reports on an empirical evaluation of the structuring method using a repository of process models from commercial practice. <s> BIB003
Process model similarity calculation is hindered by multiple inherent sources of heterogeneity. Even if two process models define exactly the same behaviour at the same level of granularity and with the same projection on the real-world process, the process models might still look quite different. We might encounter heterogeneity of behavioural representation, labelling styles, and terminology BIB001 . The first reason for this observation is that the representation of the same behaviour can be achieved with different structures. Partially, this phenomenon relates to the option to "multiply out" different choices in the process. Indeed, corresponding techniques are defined in BIB003 for making an unstructured process model structured. Therefore, we cannot assume that a different structure of process models does actually imply a difference in behaviour. Second, it has been observed that the labels can be formulated in different grammatical ways. Activities like "Send Invoice" (verb plus object) and "Sending of Invoice" (gerund plus preposition plus object) clearly point to the same type of activity. However, we cannot assume that a difference in the grammatical structure implies a difference in the activity. Techniques for automatically transforming activity labels to a canonical verb-object style are presented in BIB002 . Third, we can use syntactically different terms to defer to the same matter. For instance, two activity labels in verb-object style like "Check Invoice" and "Evaluate Bill" might use synonymous terms to refer to the same matter. Here again, we cannot assume that a difference in terms always implies a difference in meaning. Calculating the similarity of process models becomes much easier in a setting where we can assume that these heterogeneities are resolved. These issues of heterogeneous representation can be present even if two models capture one process at the same level of granularity and using the same projections. Yet, even projections and granularity may differ. In the first case, we have to deal with problems that parts of a first process model might simply be left out in a second process model. The question then becomes to which extent the calculation of similarity should punish such a difference in projection. Technically this question relates to the properties of underlying notions for similarity calculation. For the second case, we have to consider questions of granularity. In terms of similarity, it has to be decided in how far a sequence of activities in one model shall be punished when it is shown as a single abstracted activity in the second model.