Metrics for process models : empirical foundations of verification, error prediction, and guidelines for correctness

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.

In his book Jan Mendling develops a framework for the detection of formal errors in business process models and the prediction of error probability based on quality attributes of these models (metrics). He presents a precise description of Event-driven Process Chains (EPCs), their control-flow semantics and a suitable correctness criterion called EPC soundness.

1 Business Process Management	p. 1
1.1 History of Business Process Management	p. 2
1.2 Definition of Business Process Management	p. 4
1.3 Definition of Business Process Modeling	p. 7
1.4 Business Process Modeling and Errors	p. 12
1.5 Summary	p. 14
2 Event-Driven Process Chains (EPC)	p. 17
2.1 EPC Notation	p. 18
2.2 EPC Syntax	p. 20
2.2.1 Approaches to EPC Syntax Formalization	p. 21
2.2.2 Formal Syntax Definition of Flat EPCs	p. 22
2.2.3 Formal Syntax Definition of Hierarchical EPCs	p. 26
2.2.4 Formal Syntax Definition of Standard EPCs	p. 28
2.3 EPC Syntax Extensions	p. 28
2.3.1 Control Flow Extensions	p. 29
2.3.2 Configurability Extensions	p. 30
2.4 EPC Semantics	p. 30
2.4.1 Informal Semantics as a Starting Point	p. 31
2.4.2 EPC Formalization Problems	p. 31
2.4.3 Approaches to EPC Semantics Formalization	p. 34
2.4.4 EPC Semantics Based on State and Context	p. 40
2.4.5 Reachability Graph of EPCs	p. 47
2.4.6 Tool Support for EPC Semantics	p. 50
2.5 EPCs and Other Process Modeling Languages	p. 55
2.5.1 Comparison Based on Routing Elements	p. 55
2.5.2 Comparison Based on Workflow Patterns	p. 56
2.6 Summary	p. 56
3 Verification of EPC Soundness	p. 59
3.1 Soundness of EPCs	p. 59
3.1.1 Correctness Criteria for Business Process Models	p. 59
3.1.2 Definition of EPC Soundness	p. 62
3.2 Reachability Graph Verification of Soundess	p. 64
3.3 Verification by Reduction Rules	p. 67
3.3.1 Related Work on Reduction Rules	p. 69
3.3.2 A Reduction Kit for EPCs	p. 72
3.3.3 A Reduction Algorithm for EPCs	p. 91
3.3.4 Reduction of the SAP Reference Model	p. 95
3.4 Summary	p. 102
4 Metrics for Business Process Models	p. 103
4.1 Measurement Theory	p. 104
4.2 Metrics in Network Analysis	p. 107
4.3 Metrics in the Software Engineering Process	p. 110
4.4 Related Work on Metrics for Process Models	p. 114
4.5 Definition of Metrics for Process Models	p. 117
4.5.1 Size	p. 118
4.5.2 Density	p. 119
4.5.3 Partitionability	p. 121
4.5.4 Connector Interplay	p. 125
4.5.5 Cyclicity	p. 127
4.5.6 Concurrency	p. 128
4.6 Calculating Metrics	p. 130
4.7 Summary	p. 133
5 Validation of Metrics as Error Predictors	p. 135
5.1 Analysis Data Generation	p. 135
5.2 The Sample of EPC Models	p. 136
5.2.1 How Do the Four Groups Differ?	p. 137
5.2.2 How Do Correct and Incorrect Models Differ?	p. 140
5.2.3 Correlation Analysis	p. 140
5.3 Logistic Regression	p. 143
5.3.1 Introductino to Logistic Regression	p. 143
5.3.2 Preparatory Analyses	p. 144
5.3.3 Multivariate Logistic Regression Model	p. 145
5.4 External Validation	p. 147
5.5 Summary	p. 150
6 Implications for Business Process Modeling	p. 151
6.1 Seven Process Modeling Guidelines (7PMG)	p. 152
6.2 Discussion	p. 153
6.3 Future Research	p. 154
A Transition Relation of EPCs Based on State and Context	p. 155
A.1 Phase 1: Transition Relation for Dead Context Propagation	p. 155
A.2 Phase 2: Transition Relation for Wait Context Propagation	p. 156
A.3 Phase 3: Transition Relation for Negative State Propagation	p. 159
A.4 Phase 4: Transition Relation for Positive State Propagation	p. 160
References	p. 165
Index	p. 191

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