# TransformingBPMN Processes toSBVR Process Rules with
## 7 Threats to Validity  
Basic threats to the validity of our experiment results and the approach itself are categorized as follows [63]: (a) threats to construct validity, (b) threats to internal validity, and (c) threats to external validity. All three categories of threats are assessed in the following subsections.  
**Threats to Construct Validity.** To properly apply any approach, one must ensure a common understanding of things among all interested parties. However, the interpretability and common understanding of concepts throughout the problem domain have the potential to be handled improperly in certain settings; this is called a threat to construct validity. This threat was minimal in our research, because: (1) all the specified transformation rules and algorithms were automated and did not leave any space for misinterpreting things; (2) the manual extraction of benchmark experimental results was performed exclusively by the authors, who naturally shared a common understanding of things.  
**Threats to Internal Validity.** Internal validity considers internal factors and how they can affect the results, e.g., human error, motivation, subjectivity. Even though the automated nature of the experiment helped to reduce the influence of the human factor, some threats to internal validity remained.  
The manual selection of source models for the experiment might be considered one of such threats because it holds a certain degree of subjectivity. Nonetheless, the models were carefully selected by considering the variety of possible modeling cases to test various capabilities of the approach. Therefore, we state that, in this case, the subjectivity in the selection of source models was justified.  
Another threat to internal validity, which is a human error, is also related to the set of source models. As the BPMN process models were selected from different sources, neither of them was ready to be processed automatically by our experimental system. Human errors could appear during this preparation phase. However, all the inputs for the experiment were double-checked and agreed upon by all authors; therefore, we assume this threat to be minimal.  
**Threats to External Validity.** External validity can be biased by the non-rigorous generalization or failure to generalize the developed approach to a larger extent. In our case, the main threat to external validity is the fact that a relatively small number of models was selected for the experiment; this objectively reduces the reliability of the acquired experiment results to some extent.  
Another threat is the lack of standardized modeling practices, in particular, using certain conventions of naming model elements. In addition, there is always a chance that some practitioners will disagree on certain modeling practices used in this research, e.g., placing fully formulated conditions on the sequence flows diverging from a gateway instead of stating a question on the gateway itself and then placing \"yes/no\"-like answers on the diverging sequence flows. All this could lead to worse results compared with the ones presented in this paper.