Understanding Quality in Conceptual Modeling
IEEE Software
The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
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Business process models play an important role for the management, design, and improvement of process organizations and process-aware information systems. Despite the extensive application of process modeling in practice there are hardly empirical results available on quality aspects of process models. This paper aims to advance the understanding of this matter by analyzing the connection between formal errors (such as deadlocks) and a set of metrics that capture various structural and behavioral aspects of a process model. In particular we discuss the hypothetical relationship between errors and metrics, and provide a validation of correlation based on an extensive sample of EPC process models from practice. The strong connection between metrics and errors has considerable consequences for the design of future modeling guidelines and modeling tools.