Article

On a Quest for Good Process Models: The Cross-Connectivity Metric

Authors:

Irene Vanderfeesten,

Hajo A. Reijers,

Jorge CardosoAuthors Info & Claims

CAiSE '08: Proceedings of the 20th international conference on Advanced Information Systems Engineering

Pages 480 - 494

https://doi.org/10.1007/978-3-540-69534-9_36

Published: 16 June 2008 Publication History

Abstract

Business process modeling is an important corporate activity, but the understanding of what constitutes good process models is rather limited. In this paper, we turn to the cognitive dimensions framework and identify the understanding of the structural relationship between any pair of model elements as a hard mental operation. Based on the weakest-link metaphor, we introduce the cross-connectivity metric that measures the strength of the links between process model elements. The definition of this new metric builds on the hypothesis that process models are easier understood and contain less errors if they have a high cross-connectivity. We undertake a thorough empirical evaluation to test this hypothesis and present our findings. The good performance of this novel metric underlines the importance of cognitive research for advancing the field of process model measurement.

References

[1]

van der Aalst, W.M.P., ter Hofstede, A.H.M., Kiepuszewski, B., Barros, A.P.: Workflow Patterns. Distributed and Parallel Databases 14(1), 5-51 (2003).

[2]

Becker, J., Rosemann, M., von Uthmann, C.: Guidelines of Business Process Modeling. In: van der Aalst, W.M.P., Desel, J., Oberweis, A. (eds.) Business Process Management. LNCS, vol. 1806, pp. 30-49. Springer, Berlin (2000).

[3]

Bieman, J.M., Kang, B.-K.: Measuring Design-level Cohesion. IEEE Transactions on Software Engineering 24(2), 111-124.

[4]

Blackwell, A.F.: Ten Years of Cognitive Dimensions in Visual Languages and Computing. Journal of Visual Languages and Computing 17(4), 285-287 (2007).

[5]

Card, D.N., Church, V.E., Agresti, W.W.: An Empirical Study of Software Design Practices. IEEE Transactions on Software Engineering 12(2), 264-271.

[6]

Cardoso, J.: Control-flow Complexity Measurement of Processes and Weyuker's Properties. In: Proceedings of the 6th International Enformatika Conference (IEC 2005), pp. 213-218. International Academy of Sciences (2005).

[7]

Cardoso, J.: How to Measure the Control-flow Complexity of Web Processes and Workflows. In: Fischer, L. (ed.) Workflow Handbook 2005, Future Strategies, Lighthouse Point (2005).

[8]

Cardoso, J.: Process Control-flow Complexity Metric: an Empirical Validation. In: IEEE International Conference on Services Computing (IEEE SCC 2006), pp. 167-173. IEEE Computer Society Press, Los Alamitos (2006).

[9]

Cardoso, J., Mendling, J., Neumann, G., Reijers, H.A.: A Discourse on Complexity of Process Models. In: Eder, J., Dustdar, S. (eds.) BPM Workshops 2006. LNCS, vol. 4103, pp. 115-126. Springer, Heidelberg (2006).

[10]

Daneva, M., Heib, R., Scheer, A.-W.: Benchmarking Business Process Models. IWi Research Report 136, Institute for Information Systems, University of the Saarland, Germany (1996).

[11]

Green, T.R.G., Petre, M.: Usability Analysis of Visual Programming Environments: A 'Cognitive Dimensions' Framework. Journal of Visual Languages and Computing 7(2), 131-174 (1996).

[12]

Gruhn, V., Laue, R.: Complexity Metrics for Business Process Models. In: Proceedings of the 9th international conference on business information systems (BIS 2006). Lecture Notes in Informatics, vol. 85 (2006).

[13]

Hosmer, D., Lemeshow, S.: Applied Logistic Regression, 2nd edn. Wiley & Sons, Chichester (2000).

[14]

Kafura, D.: A Survey of Software Metrics. In: ACM 1985: Proceedings of the 1985 ACM annual conference on The range of computing: mid-80's perspective, pp. 502-506. ACM Press, New York (1985).

[15]

Kang, B.-K., Bieman, J.M.: A Quantitative Framework for Software Restructuring. Journal of Software Maintenance 11, 245-284 (1999).

[16]

Kawalek, P., Kueng, P.: The Usefulness of Process Models: A Lifecycle Description of how Process Models are used in Modern Organisations. In: Siau, K., Wand, Y., Parsons, J. (eds.) Proceedings of the Second CAiSE/IFIP8.1 International Workshop on Evaluation of Modelling Methods in Systems Analysis and Design, pp. 1-12 (1997).

[17]

Keller, G., Teufel, T.: Sap R/3 Process Oriented Implementation: Iterative Process Prototyping. Addison-Wesley Longman Publishing Co., Inc, Boston (1998).

[18]

Krogstie, J., Sindre, G., Jørgensen, H.: Process Models Representing Knowledge for Action: a Revised Quality Framework. European Journal of Information Systems 15(1), 91-102 (2006).

[19]

Lindsay, A., Downs, D., Lunn, K.: Business processes: attempts to find a definition. Information and Software Technology 45(15), 1015-1019 (2003).

[20]

Mendling, J.: Detection and Prediction of Errors in EPC Business Process Models. PhD thesis, Vienna University of Economics and Business Administration, Vienna, Austria (May 2007).

[21]

Mendling, J., van der Aalst, W.M.P.: Formalization and Verification of EPCs with OR-Joins Based on State and Context. In: Krogstie, J., Opdahl, A., Sindre, G. (eds.) CAiSE 2007 and WES 2007. LNCS, vol. 4495, pp. 439-453. Springer, Berlin (2007).

[22]

Mendling, J., Neumann, G., van der Aalst, W.M.P.: Understanding the Occurrence of Errors in Process Models based on Metrics. In: Meersman, R., Tari, Z. (eds.) OTM 2007, Part I. LNCS, vol. 4803, pp. 113-130. Springer, Heidelberg (2007).

[23]

Mendling, J., Reijers, H.A., Cardoso, J.: What Makes Process Models Understandable? In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 48-63. Springer, Berlin (2007).

[24]

Mendling, J., Verbeek, H.M.W., van Dongen, B.F., van der Aalst, W.M.P., Neumann, G.: Detection and Prediction of Errors in EPCs of the SAP Reference Model. Data and Knowledge Engineering 64(1), 312-329 (2008).

[25]

Morasca, S.: Measuring Attributes of Concurrent Software Specifications in Petrinets. In: Proceedings of the 6th International Symposium on Software Metrics, pp. 100-110. IEEE Computer Society, Los Alamitos (1999).

[26]

Ould, M.A.: Business Processes: Modelling and Analysis for Re-engineering and Improvement. Wiley, Chichester (1995).

[27]

Reijers, H.A.: A Cohesion Metric for the Definition of Activities in a Workflow Process. In: Proceedings of the 8th CAiSE/IFIP8.1 International workshop on Evaluation of Modeling Methods in Systems Analysis and Design (EMMSAD 2003), pp. 116-125 (2003).

[28]

Reijers, H.A., Vanderfeesten, I.T.P.: Cohesion and Coupling Metrics for Workflow Process Design. In: Desel, J., Pernici, B., Weske, M. (eds.) BPM 2004. LNCS, vol. 3080, pp. 290-305. Springer, Berlin (2004).

[29]

Rosemann, M.: Potential Pitfalls of Process Modeling: Part A. Business Process Management Journal 12(2), 249-254 (2006).

[30]

Rosemann, M.: Potential Pitfalls of Process Modeling: Part B. Business Process Management Journal 12(3), 377-384 (2006).

[31]

Selby, R.W., Basili, V.R.: Analyzing Error-Prone System Structure. IEEE Transactions on Software Engineering 17, 141-152 (1991).

[32]

Shen, V.Y., Yu, T.-J., Thebaut, S.M., Paulsen, L.R.: Identifying Error-Prone Software. IEEE Transactions on Software Engineering 11, 317-324 (1985).

[33]

Vanderfeesten, I., Cardoso, J., Mendling, J., Reijers, H.A., van der Aalst, W.M.P.: Quality Metrics for Business Process Models. In: Fischer, L. (ed.) BPM and Workflow Handbook 2007, Future Strategies, USA, May 2007, pp. 179-190 (2007).

[34]

Vanderfeesten, I., Cardoso, J., Reijers, H.A.: A Weighted Coupling Metric for Business Process Models. In: Eder, J., Tomassen, S.L., Opdahl, A., Sindre, G. (eds.) Proceedings of the CAiSE 2007 Forum, CEUR Workshop Proceedings, vol. 247, pp. 41-44 (2007).

[35]

Xenos, M., Stavrinoudis, D., Zikouli, K., Christodoulakis, D.: Object-Oriented Metrics - A Survey. In: Proceedings of the FESMA 2000, Federation of European Software Measurement Associations, pp. 1-10 (2000).

Cited By

Fakorede ODavies P(2020)Quantitative Measurable Concepts to Visualize Business Process ImprovementProceedings of the 3rd International Conference on Big Data Technologies10.1145/3422713.3422753(147-154)Online publication date: 18-Sep-2020
https://dl.acm.org/doi/10.1145/3422713.3422753
Lux MRinderle-Ma SPreda A(2018)Assessing the Quality of Search Process ModelsBusiness Process Management10.1007/978-3-319-98648-7_26(445-461)Online publication date: 9-Sep-2018
https://dl.acm.org/doi/10.1007/978-3-319-98648-7_26
Polani GCegnar B(2017)Complexity metrics for process models A systematic literature reviewComputer Standards & Interfaces10.1016/j.csi.2016.12.00351:C(104-117)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1016/j.csi.2016.12.003
Show More Cited By

On a Quest for Good Process Models: The Cross-Connectivity Metric
1. Applied computing
  1. Enterprise computing

Recommendations

Improved model management with aggregated business process models

Contemporary organizations invest much efforts in creating models of their business processes. This raises the issue of how to deal with large sets of process models that become available over time. This paper proposes an extension of Event-driven ...
Coupling metrics for business process modeling

Modeling business processes is vital when improving or automating existing business processes, documenting processes properly or comparing business processes. In addition, it is necessary to evaluate the quality of a business process model through a set ...
Quality metrics for business process modeling
ACS'09: Proceedings of the 9th WSEAS international conference on Applied computer science

Modeling business processes is vital when improving or automating existing business pocesses, documenting processes properly or comparing business processes. In addition, it is necessary to be able to evaluate the quality of a business process model, ...

Comments

Information & Contributors

Information

Published In

cover image Guide Proceedings

CAiSE '08: Proceedings of the 20th international conference on Advanced Information Systems Engineering

June 2008

586 pages

ISBN:9783540695332

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 16 June 2008

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

11
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 23 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Fakorede ODavies P(2020)Quantitative Measurable Concepts to Visualize Business Process ImprovementProceedings of the 3rd International Conference on Big Data Technologies10.1145/3422713.3422753(147-154)Online publication date: 18-Sep-2020
https://dl.acm.org/doi/10.1145/3422713.3422753
Lux MRinderle-Ma SPreda A(2018)Assessing the Quality of Search Process ModelsBusiness Process Management10.1007/978-3-319-98648-7_26(445-461)Online publication date: 9-Sep-2018
https://dl.acm.org/doi/10.1007/978-3-319-98648-7_26
Polani GCegnar B(2017)Complexity metrics for process models A systematic literature reviewComputer Standards & Interfaces10.1016/j.csi.2016.12.00351:C(104-117)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1016/j.csi.2016.12.003
Marin MLotriet HVan Der Poll J(2015)Metrics for the Case Management Modeling and Notation (CMMN) SpecificationProceedings of the 2015 Annual Research Conference on South African Institute of Computer Scientists and Information Technologists10.1145/2815782.2815813(1-10)Online publication date: 28-Sep-2015
https://dl.acm.org/doi/10.1145/2815782.2815813
Dumas MLa Rosa MMendling JMäesalu RReijers HSemenenko N(2012)Understanding business process modelsProceedings of the 24th international conference on Advanced Information Systems Engineering10.1007/978-3-642-31095-9_3(31-46)Online publication date: 25-Jun-2012
https://dl.acm.org/doi/10.1007/978-3-642-31095-9_3
Smirnov SReijers HWeske M(2011)A semantic approach for business process model abstractionProceedings of the 23rd international conference on Advanced information systems engineering10.5555/2026716.2026764(497-511)Online publication date: 20-Jun-2011
https://dl.acm.org/doi/10.5555/2026716.2026764
Sánchez-González LRuiz FGarcía FCardoso JChu WWong WPalakal MHung C(2011)Towards thresholds of control flow complexity measures for BPMN modelsProceedings of the 2011 ACM Symposium on Applied Computing10.1145/1982185.1982496(1445-1450)Online publication date: 21-Mar-2011
https://dl.acm.org/doi/10.1145/1982185.1982496
Reijers HMendling JDijkman R(2011)Human and automatic modularizations of process models to enhance their comprehensionInformation Systems10.1016/j.is.2011.03.00336:5(881-897)Online publication date: 1-Jul-2011
https://dl.acm.org/doi/10.1016/j.is.2011.03.003
Jung JChin CCardoso J(2011)An entropy-based uncertainty measure of process modelsInformation Processing Letters10.1016/j.ipl.2010.10.022111:3(135-141)Online publication date: 1-Jan-2011
https://dl.acm.org/doi/10.1016/j.ipl.2010.10.022
Weber BReichert MMendling JReijers H(2011)Survey paperComputers in Industry10.1016/j.compind.2010.12.01262:5(467-486)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1016/j.compind.2010.12.012
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Table of Contents