Exploring Complexity Metrics for Artifact-Centric Business Process Models

433 Pages·2017·4 MB·English

by  Mike Andy Marin

Exploring Complexity Metrics for
Artifact-Centric Business Process Models
by
Mike Andy Marin
submitted in accordance with the requirements for the degree of
Doctor of Philosophy
in the subject
Computer Science
at the
UNIVERSITY OF SOUTH AFRICA
Supervisor: Professor Hugo Lotriet
Co-supervisors: Professor John A. Van Der Poll
Professor Peter M. Njuho
February 2017

Declaration of Authorship
I,MikeAndyMarin,declarethatthisthesistitled,‘ExploringComplexityMetricsforArtifact-
Centric Business Process Models’ is my own work and that all the sources that I have used
or quoted have been indicated and acknowledged by means of complete references.
Signed:
Date:
iii
iv
”I’ve never been a good estimator of how long things are going to take.”
Donald Knuth
Abstract
This study explores complexity metrics forbusiness artifactprocess models describedby Case
Management Model and Notation (CMMN). Process models are usually described using
Business Process Management (BPM), which is a relatively mature discipline with a large
number of practitioners. Over the last few decades a new way of describing data intensive
business processes has emerged in BPM literature, for which traditional BPM is no longer
adequate. This emerging method, used to describe more flexible processes, is called business
artifacts with Guard-Stage-Milestone (GSM). The work on GSM influenced CMMN, which
was created to fill a market need for more flexible case management processes for knowledge
workers.
Complexity metrics have been developed for traditional BPM models, such as the Business
ProcessModelandNotation(BPMN). However,traditionalBPMisnotsuitablefordescribing
GSM or CMMN process models. Therefore, complexity metrics developed for traditional
process models may not be applicable to business artifact process models such as CMMN.
This study addresses this gap by exploring complexity metrics for business artifact process
models using CMMN. The findings of this study have practical implications for the CMMN
standard and for the commercial products implementing CMMN. This research makes the
following contributions:
• The development of a formal description of CMMN using first-order logic.
• An exploration of the relationship between CMMN and GSM and the development of
transformation procedures between them.
• A comparison between the method complexity of CMMN and other popular process
methods, including BPMN, Unified Modeling Language (UML) Activity diagrams, and
Event-driven Process Charts (EPC).
• The creation of a systematic literature review of complexity metrics for process models,
which was conducted in order to inform the creation of CMMN metrics.
• The identification of a set of complexity metrics for the CMMN standard, which under-
went theoretical and empirical validation.
This research advances literature in the areas of method complexity, complexity metrics
for process models, declarative processes, and research on CMMN by characterizing CMMN
methodcomplexity, identifying complexitymetrics forCMMN, andexploring the relationship
between CMMN and GSM.
Keywords: Business Artifacts, Business Process Management, BPM, Business Process
Model, Case Management, Case Management Model and Notation, CMMN, Guard-Stage-
Milestone, GSM, Complexity Metric, Process Model Complexity, Method Complexity
Acknowledgements
This thesis is the product of a very long and arduous journey, but one with many interesting
detours that have taken me to places, both intellectually and physically, that I had never
imagined. The last part of this journey brought me and my wife to South Africa, a beautiful
country with great people and wonderful cultures. This thesis would not have been possible
without the help of so many people who I would like to sincerely thank for having assisted
me with completing my research.
First and foremost, my sincerest gratitude goes to my supervisors Professor Hugo Lotriet and
ProfessorJohn A. Van DerPollfortheirexpertguidance andassistance. I’m also indebtedto
Professor Peter M. Njuho for his support and guidance on how to select the correct research
design and statistical analysis for the empirical validation.
I would also like to thank Estelle de Kock who not only helped me navigate UNISA’s rules
and regulations, but provided invaluable information when we decided to move to South
Africa, and Filistéa Naudé for her valuable support in obtaining the hard to find literature
for this study.
ThereareseveralIBMerswhoIwouldalsoliketomentionhere. CristianeHilknerwhoworked
hard to secure the sabbatical that made it possible for me to complete this thesis. Richard
Hull who has always been willing to help with all sorts of activities, including: crafting a
standard,answeringquestions,orfindingsubjectsforthesurvey. Iwouldalsoliketothankmy
IBM colleagues from all over the world who were always willing to help me. Special mention
goes to Martin Dwane who put forward the idea of the sabbatical, Diane McPhee and Darik
Siegfried who read and provided feedback on the tutorial, and to those who participated in
the pilot study.
Iamalsogratefultothemanypeoplewhohelpedmepromotethesurveyandtutorialincluding
Leila Neimane, Sandy Kemsley, Paul Harmon, Richard Hull, Keith Swenson, Marlon Dumas,
Matthias Kloppmann.
Finally, this journey and thesis could not have happened without the love, unfailing loyalty
and many sacrifices made by my wife, Anabelle. Words cannot express how grateful I am to
her for following me and my crazy ideas all over the world, and for our two great kids.
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Contents
Title i
Declaration of Authorship iii
Abstract v
Acknowledgements vi
Contents vii
List of Figures xi
List of Tables xiii
Acronyms xvii
Symbols xxi
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Objectives and Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.1 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.2 Significance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.5 Previous Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2 Background 11
2.1 Business Process Management . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.1 Process Lifecycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2 Business Process Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2.1 Process Modeling Notations . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.2 Modeling Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.2.2.1 Modeling Dimensions . . . . . . . . . . . . . . . . . . . . . . 20
2.2.3 Process Modeling Metrics . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3 Case Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.4 Business Artifacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.4.1 Finite-State Machine Based Lifecycles . . . . . . . . . . . . . . . . . . 32
2.4.2 Declarative Life Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.4.3 The Case Management Model and Notation . . . . . . . . . . . . . . . 37
2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
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Contents viii
3 Business Artifacts and Case Management 39
3.1 Business Artifacts with Lifecycle Services and Associations . . . . . . . . . . 39
3.2 Guard-Stage-Milestone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.2.1 Artifact Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.2.1.1 Operational Semantics. . . . . . . . . . . . . . . . . . . . . . 46
3.2.2 Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.3 Case Management Model and Notation . . . . . . . . . . . . . . . . . . . . . 48
3.3.1 Case Type. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.3.2 Case Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.3.3 Case Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.3.3.1 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.4 Differences between GSM and CMMN . . . . . . . . . . . . . . . . . . . . . . 59
3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4 Case Management Model and Notation Method Complexity 65
4.1 Method Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4.2.1 Meta-Model-Based Method Complexity . . . . . . . . . . . . . . . . . 69
4.2.1.1 Adjustments . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
4.2.1.2 Counting Principles . . . . . . . . . . . . . . . . . . . . . . . 71
4.3 CMMN Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.4 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.4.1 Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
5 Transformations Between GSM and CMMN 77
5.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
5.2 Transforming an Artifact Type into a Case Type . . . . . . . . . . . . . . . . 79
5.2.1 Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.3 Transforming a Case Type into an Artifact Type . . . . . . . . . . . . . . . . 84
5.3.1 Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5.3.1.1 Case Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.3.1.2 Data Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.3.1.3 Stages and Tasks Patterns . . . . . . . . . . . . . . . . . . . 91
5.3.1.4 Milestone and Event Listener Patterns . . . . . . . . . . . . 91
5.3.1.5 Rule Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.3.1.6 Discretionary Item Pattern . . . . . . . . . . . . . . . . . . . 96
5.3.1.7 Parallel Execution Pattern . . . . . . . . . . . . . . . . . . . 96
5.3.1.8 Sentry Related Patterns and Transformation . . . . . . . . . 97
5.3.2 Transformation Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
6 Systematic Literature Review of Process Modeling Complexity Metrics 103
6.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.1.1 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.1.2 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
6.1.3 Validation of Process Metrics . . . . . . . . . . . . . . . . . . . . . . . 106
Contents ix
6.2 Review Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6.3 Review Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
6.3.1 Data Sources and Search Strategy . . . . . . . . . . . . . . . . . . . . 109
6.3.2 Study Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
6.3.3 Data Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
6.3.4 Study Quality Assessment . . . . . . . . . . . . . . . . . . . . . . . . . 111
6.3.5 Data Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
6.3.6 Included and Excluded Studies . . . . . . . . . . . . . . . . . . . . . . 114
6.4 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
6.4.1 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
6.4.1.1 Complexity Metrics Identified in the Literature (RQ1) . . . . 121
6.4.1.2 Research Methods used to Validate Complexity Metrics (RQ2)123
6.4.1.3 Validating Complexity Metrics (RQ3) . . . . . . . . . . . . . 125
6.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
6.5.1 Principal Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.5.2 Strengths and Weaknesses . . . . . . . . . . . . . . . . . . . . . . . . . 132
6.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
7 Metrics for Case Management 135
7.1 Applicability of Current Process Metrics to Case Management Modeling and
Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
7.2 Defining Metrics for Case Management Modeling and Notation . . . . . . . . 138
7.3 Theoretical Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
7.3.1 Briand’s Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
7.3.1.1 Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
7.3.1.2 Length . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
7.3.1.3 Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
7.3.2 Weyuker’s Properties. . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
7.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
8 Empirical Validation of Case Management Metrics 157
8.1 Empirical Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
8.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
8.2.1 Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
8.2.2 Operational Definition of Variables . . . . . . . . . . . . . . . . . . . . 161
8.2.2.1 Independent Variables . . . . . . . . . . . . . . . . . . . . . . 162
8.2.3 Experimental Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
8.2.3.1 Model Comprehension . . . . . . . . . . . . . . . . . . . . . . 164
8.2.3.2 Perceived Complexity . . . . . . . . . . . . . . . . . . . . . . 166
8.2.3.3 Perceived Complexity and Model Comprehension . . . . . . 167
8.2.3.4 Pairwise Comparison . . . . . . . . . . . . . . . . . . . . . . 169
8.2.3.5 Complexity Weights Validation . . . . . . . . . . . . . . . . . 173
8.2.4 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
8.2.4.1 Ethical Considerations . . . . . . . . . . . . . . . . . . . . . 178
8.2.5 Research Instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
8.2.5.1 Data Description . . . . . . . . . . . . . . . . . . . . . . . . . 179
8.2.6 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
Contents x
8.2.6.1 Minimizing Threats to Validity . . . . . . . . . . . . . . . . . 180
8.2.7 Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
8.3 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
8.3.1 Sample Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
8.3.2 Normality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
8.3.3 Times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
8.3.4 Hypothesis Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
8.3.4.1 Model Comprehension . . . . . . . . . . . . . . . . . . . . . . 184
8.3.4.2 Perceived Complexity . . . . . . . . . . . . . . . . . . . . . . 186
8.3.4.3 Perceived Complexity and Model Comprehension . . . . . . 186
8.3.4.4 Pairwise Comparison . . . . . . . . . . . . . . . . . . . . . . 187
8.3.4.5 Complexity Weights Validation . . . . . . . . . . . . . . . . . 188
8.3.5 Measurement Validity . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
8.3.6 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
8.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
9 Conclusion and Future Areas for Investigation 193
9.1 Discussion of Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
9.2 Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
9.3 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
9.4 Recommendations for Future Research . . . . . . . . . . . . . . . . . . . . . . 198
9.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
Bibliography 201
Glossary 251
Index 290
A GSM to CMMN Syntax Directed Translation Grammar 299
A.1 Grammar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299
A.2 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302
B Process Modeling Complexity Metrics 305
B.1 Identified Papers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
B.2 Identified Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358
C Ethical Clearance Approval Letter 387
D Supplementary Material 389
D.1 Data Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389
D.2 Documents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 390
D.3 Systematic Literature Review of Metrics . . . . . . . . . . . . . . . . . . . . . 392
D.4 Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393
D.4.1 R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393
D.4.2 eXeLearning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 394
D.4.3 LimeSurvey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395
D.4.4 MiniZinc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395