Quality assessment of business process models based on thresholds

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6426 LNCS, Issue PART 1, 2010, Pages 78-95

  Sánchez González, Laura ^a   García, Félix ^a   Mendling, Jan ^b   Ruiz, Francisco ^a  

^a UNIVERSITY OF CASTILLA LA MANCHA   (Spain)

^b HUMBOLDT UNIVERSITY   (Germany)

Author keywords

BPMN; Business process; Correlation analysis; Measurement; Regression analysis

Indexed keywords

BENEFITS AND COSTS; BPMN; BUSINESS MODELS; BUSINESS PROCESS; BUSINESS PROCESS DESIGN; BUSINESS PROCESS MODEL; CORRELATION ANALYSIS; DYNAMIC ENVIRONMENTS; MODIFIABILITY; POSTERIORI; PROCESS IMPROVEMENT; PROCESS MODEL; PROCESS MODELLING; QUALITY ASSESSMENT; QUALITY ATTRIBUTES; STRUCTURAL METRICS; UNDERSTANDABILITY; CORRELATION AND REGRESSION ANALYSIS; PROCESS MODEL QUALITIES;

INTERNET; QUALITY ASSURANCE; QUALITY CONTROL; REGRESSION ANALYSIS; STATISTICS; MEASUREMENTS; PROCESS ENGINEERING; QUALITY MANAGEMENT;

PROCESS DESIGN;

EID: 78650085920     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-16934-2_9     Document Type: Conference Paper

References (44)

1. Pfleeger, S.L.: Integrating Process and Measurement. In: Melton, A. (ed.) Software Measurement, pp. 53-74. International Thomson Computer Press (1996)
2. Rosemann, M.: Potential pitfalls of process modeling: part A. Business Process Management Journal 12(2), 249-254 (2006)
3. Indulska, M., Green, P., Recker, J., Rosemann, M.: Business Process Modeling: Perceived Benefits. In: Laender, A.H.F. (ed.) ER 2009. LNCS, vol. 5829, pp. 458-471. Springer, Heidelberg (2009)
4. Moody, D.: Theoretical and practical issues in evaluating the quality of conceptual models: current state and future directions. Data and Knowledge Engineering, 55, 243-276 (2005)
5. Mylopoulos, J.: Conceptual modeling and telos. In: Conceptual Modeling, Databases, and Case: an Integrated View of Information Systems Development, ch. 2, pp. 49-68 (1992)
6. Dandekar, A., Perry, D.E., Votta, L.G.: Studies in Process Simplification. In: Proceedings of the Fourth International Conference on the Software Process, pp. 27-35 (1996)
7. ISO/IEC, ISO Standard 9000-2000: Quality Management Systems: Fundamentals and Vocabulary (2000)
8. ISO/IEC, 9126-1, Software engineering - product quality - Part 1: Quality Model (2001)
9. Sánchez González, L., García, F., Ruiz, F., Piattini, M.: Measurement in Business Processes: a Systematic Review. Business Process Management Journal 16(1), 114-134 (2010)
10. Zelkowitz, M., Wallace, D.: Esperimental models for validating technology. IEEE Computer, Computing practices (1998)
11. Mendling, J.: Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness. Springer Publishing Company, Incorporated, Heidelberg (2008)
12. OMG. Business Process Modeling Notation (BPMN), Final Adopted Specification (2006), http://www.omg.org/bpm
13. Gilmore, D., Green, T.: Comprehension and Recall of miniature programs. International Jounal of Man-Machine Studies archive 21(1), 31-48 (1984)
14. Rittgen, P.: Negotiating Models. In: Krogstie, J., Opdahl, A.L., Sindre, G. (eds.) CAiSE 2007 and WES 2007. LNCS, vol. 4495, pp. 561-573. Springer, Heidelberg (2007)
15. Rosemann, M.: Potential pitfalls of process modeling: part B. Business Process Management Journal 12(3), 377-384 (2006)
16. 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, Heidelberg (2007)
17. Green, T.R.G., Petre, M.: Usability analysis of visual programming environments: a cognitive dimensions framework. J. Visual Languages and Computing 7, 131-174 (1996)
18. Experiments (2009), http://alarcos.inf-cr.uclm.es/bpmnexperiments/
19. Foss, T., Stensrud, E., Kitchenham, B., Myrtveit, I.: A Simulation Study of the Model Evaluation Criterion MMRE. IEEE Transactions on Software Engineering 29, 985-995 (2003)
20. Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering, T. report, Editor, Keele University and University of Durham (2007)
21. Cardoso, J.: Process control-flow complexity metric: An empirical validation. In: SCC 2006: Proceedings of the IEEE International Conference on Services Computing, pp. 167-173 (2006)
22. Rolón, E., García, F., Ruiz, F.: Evaluation Measures for Business Process Models. In: Symposium in Applied Computing SAC 2006 (2006)
23. Rolón, E., Cardoso, J., García, F., Ruiz, F., Piattini, M.: Analysis and Validation of Control-Flow Complexity Measures with BPMN Process Models. In: The 10th Workshop on Business Process Modeling, Development, and Support (2009)
24. Rolón, E., Ruiz, F., García, F., Piattini, M.: Applying Software Process Metrics in Business Process. Procesos y Métricas, Asociación Española de Métricas del Software 3(2) (2006)
25. Rolon, E., Sanchez, L., Garcia, F., Ruiz, F., Piattini, M., Caivano, D., Visaggio, G.: Prediction Models for BPMN Usability and Maintainability. In: BPMN 2009 - 1st International Workshop on BPMN, pp. 383-390 (2009)
26. Vanderfeesten, I., Reijers, H.A., van der Aalst, W.M.P.: Evaluating Workflow Process Designs using Cohesion and Coupling Metrics. In: Computer in Industry (2008)
27. Vanderfeesten, I., Reijers, H.A., Mendling, J., van der Aalst, W.M.P., Cardoso, J.: On a Quest for Good Process models: the Cross Conectivity Metric. In: Bellahsène, Z., Léonard, M. (eds.) CAiSE 2008. LNCS, vol. 5074, pp. 480-494. Springer, Heidelberg (2008)
28. Mendling, J.: Testing Density as a complexity Metric for EPCs, in Technical Report JM-2006-11-15 (2006)
29. Cardoso, J.: How to Measure the Control-Flow Complexity of Web Processes and Workflows. In: Workflow Handbook 2005 (2005)
30. Cardoso, J.: Business Process Quality Metrics: Log-based Complexity of Workflow Patterns. In: Meersman, R., Tari, Z. (eds.) OTM 2007, Part I. LNCS, vol. 4803, pp. 427-434. Springer, Heidelberg (2007)
31. Jung, J.Y.: Measuring entropy in business process models. In: International Conference on Innovative Computing, Information and Control, pp. 246-252 (2008)
32. Latva-Koivisto, A.M.: Finding a Complexity Measure for Business Process Models. Individual Research Projects in Applied Mathematics (2001)
33. Gruhn, V., Laue, R.: Complexity Metrics for business Process Models. In: International Conference on Business Information Systems (2006)
34. Gruhn, V., Laue, R.: Adopting the Cognitive Complexity Measure for Business Process Models. In: 5th IEEE International Conference on Cognitive Informatics, ICCI 2006, vol. 1, pp. 236-241 (2006)
35. Rozinat, A., van der Aalst, W.M.P.: Conformance checking of processes based on monitoring real behavior. Information Systems 33, 64-95 (2008)
36. Laue, R., Mendling, J.: Structuredness and its Significance for Correctness of Process Models. In: Information Systems and E-Business Management (2009)
37. Meimandi Parizi, R., Ghani, A.A.A.: An Ensemble of Complexity Metrics for BPEL Web Processes. In: Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, pp. 753-758 (2008)
38. Bisgaard Lassen, K., Van der Aalst, W.: Complexity Metrics for Workflow Nets. In: Information and Software Technology, pp. 610-626 (2008)
39. Huan, Z., Kumar, A.: New quality metrics for evaluating process models. In: Business Process Intelligence Workshop (2008)
40. Henderson-Sellers, B.: Object-Oriented Metrics: Measures of Complexity. Prentice-Hall, Englewood Cliffs (1996)
41. Shatnawi, R., Li, W., Swain, J., Newman, T.: Finding Software Metrics Threshold values using ROC Curves. In: Sofware Maintenance and Evolution: Research and Practice (2009)
42. Churchill, G.A., Doerge, R.W.: Empirical Threshold Values for Quantitative Trait Mapping. Genetics Society of America 138, 963-971 (1995)
43. Bender, R.: Quantitative Risk Assessment in Epidemiological Studies Investigatin Threshold Effects. Biometrical Journal 41(3), 305-319 (1999)
44. Royston, P., Douglas, G.A., Sauerbrei, W.: Dichotomizing continuous predictors in multiple regression: a bad idea. Statistics in Medicine 25, 127-141 (2005)