Lecture Notes in Business Information Processing Series Editors Wil van der Aalst Eindhoven Technical University, The Netherlands John Mylopoulos University of Trento, Italy Norman M. Sadeh Carnegie Mellon University, Pittsburgh, PA, USA Michael J. Shaw University of Illinois, Urbana-Champaign, IL, USA Clemens Szyperski Microsoft Research, Redmond, WA, USA
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Jan Mendling
Metrics for Process Models Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness
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Author Jan Mendling Humboldt-Universität zu Berlin Institut für Wirtschaftsinformatik Spandauer Str. 1, 10178 Berlin, Germany E-mail:
[email protected]
Library of Congress Control Number: 2008938155 ACM Computing Classification (1998): H.4, J.1, D.2 ISSN ISBN-10 ISBN-13
1865-1348 3-540-89223-0 Springer Berlin Heidelberg New York 978-3-540-89223-6 Springer Berlin Heidelberg New York
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To Leni and to my family
Preface
Business process modeling plays an important role in the management of business processes. As valuable design artifacts, business process models are subject to quality considerations. The absence of formal errors such as deadlocks is of paramount importance for the subsequent implementation of the process. This book develops a framework for the detection of formal errors in business process models and for the prediction of error probability based on quality attributes of these models (metrics). We focus on Event-driven Process Chains (EPCs), a widely used business process modeling language due to its extensive tool support. The advantage of this focus is firstly that the results of this book can be directly translated into process modeling practice. Secondly, there is a large empirical basis of models. By utilizing this large stock of EPC model collections, we aim to bring forth general insights into the connection between process model metrics and error probability. In order to validate such a connection, we first need to establish an understanding of which model attributes are likely connected with error probability. Furthermore, we must formally define an appropriate notion of correctness that answers th