Process modeling is an indispensable task in the discipline of Business Process Management. The process models created in this task help its readers in to acquiring a higher comprehension of a process, allowing for the discovery of opportunities for its improvement. However, the comprehension of a process model is not guaranteed, as process modeling is a complex task that depends on the proficiency of the process modeler to avoid the creation of badly designed constructs. Process modeling guidelines are an essential tool in this regard, though they are dispersed across the many studies of the literature and not all of them have empirical evidence validating their effects. In addition to this problem, it is still an open questions if a set of process modeling guidelines makes the process modeling task more challenging and how effective modelers are in using them. It is also unclear how receptive process analysts are to the modeling guidelines. This dissertation presents a systematic literature review we conducted to collect and analyze the modeling guidelines found in the literature. It investigated a total of 520 articles, extracting a total of 45 modeling guidelines spread across 4 different categories. These 45 guidelines were simplified into a set of 20 guidelines, based on their significance to create more comprehensible process models and their practicality. This dissertation also presents the findings of an empirical experiment performed by 13 subjects that compared the results of two process modeling tasks with and without the support of the 20 modeling guidelines presented by the review, in which it was possible to observe that the subjects recognize the usefulness of the guidelines, but find them difficult to understand and use.

Companies increasingly use business process modeling for documenting and redesigning their operations. However, due to the size of such modeling initiatives, they often struggle with the quality assurance of their model collections. While many model properties can already be checked automatically, there is a notable gap of techniques for checking linguistic aspects such as naming conventions of process model elements. In this paper, we address this problem by introducing an automatic technique for detecting violations of naming conventions. This technique is based on text corpora and independent of linguistic resources such as WordNet. Therefore, it can be easily adapted to the broad set of languages for which corpora exist. We demonstrate the applicability of the technique by analyzing nine process model collections from practice, including over 27,000 labels and covering three different languages. The results of the evaluation show that our technique yields stable results and can reliably deal with ambiguous cases. In this way, this paper provides an important contribution to the field of automated quality assurance of conceptual models.

Process modeling is an indispensable task in the discipline of Business Process Management. The process models created in this task help its readers in to acquiring a higher comprehension of a process, allowing for the discovery of opportunities for its improvement. However, the comprehension of a process model is not guaranteed, as process modeling is a complex task that depends on the proficiency of the process modeler to avoid the creation of badly designed constructs. Process modeling guidelines are an essential tool in this regard, though they are dispersed across the many studies of the literature and not all of them have empirical evidence validating their effects. In addition to this problem, it is still an open questions if a set of process modeling guidelines makes the process modeling task more challenging and how effective modelers are in using them. It is also unclear how receptive process analysts are to the modeling guidelines. This dissertation presents a systematic literature review we conducted to collect and analyze the modeling guidelines found in the literature. It investigated a total of 520 articles, extracting a total of 45 modeling guidelines spread across 4 different categories. These 45 guidelines were simplified into a set of 20 guidelines, based on their significance to create more comprehensible process models and their practicality. This dissertation also presents the findings of an empirical experiment performed by 13 subjects that compared the results of two process modeling tasks with and without the support of the 20 modeling guidelines presented by the review, in which it was possible to observe that the subjects recognize the usefulness of the guidelines, but find them difficult to understand and use.

Process modeling is an indispensable task in the discipline of Business Process Management. The process models created in this task help its readers in to acquiring a higher comprehension of a process, allowing for the discovery of opportunities for its improvement. However, the comprehension of a process model is not guaranteed, as process modeling is a complex task that depends on the proficiency of the process modeler to avoid the creation of badly designed constructs. Process modeling guidelines are an essential tool in this regard, though they are dispersed across the many studies of the literature and not all of them have empirical evidence validating their effects. In addition to this problem, it is still an open questions if a set of process modeling guidelines makes the process modeling task more challenging and how effective modelers are in using them. It is also unclear how receptive process analysts are to the modeling guidelines. This dissertation presents a systematic literature review we conducted to collect and analyze the modeling guidelines found in the literature. It investigated a total of 520 articles, extracting a total of 45 modeling guidelines spread across 4 different categories. These 45 guidelines were simplified into a set of 20 guidelines, based on their significance to create more comprehensible process models and their practicality. This dissertation also presents the findings of an empirical experiment performed by 13 subjects that compared the results of two process modeling tasks with and without the support of the 20 modeling guidelines presented by the review, in which it was possible to observe that the subjects recognize the usefulness of the guidelines, but find them difficult to understand and use.