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University of Stuttgart
Universitätsstr. 38
70569 Stuttgart
Germany
Phone +49-711-685 88477
Fax +49-711-685 88472
Research...
22
Research
© Marigianna Skouradaki
BPMN 2.0
Process Models
Collection
Fragments
Repository
Workload
Mix
Graph
Matching
Se...
33
Research
© Marigianna Skouradaki
Agenda
 Process Model Matching
 Basic Concepts
 Algorithm
 Evaluation & Validation...
4
Process Matching
55
Research
© Marigianna Skouradaki
BPMN 2.0 Collection Characteristics
 Detect the reoccurring structures on BPMN 2.0 pr...
66
Research
© Marigianna Skouradaki
Text Matching
 Cannot be applied to anonymized models
88
Research
© Marigianna Skouradaki
Matching Executional Information
log
 Comparing produced execution logs
Cannot be app...
99
Research
© Marigianna Skouradaki
Structural Matching
1010
Research
© Marigianna Skouradaki
The Challenge of Graph Isomorphism
NonDeterministic Polynomial
Time
(NP – Complete)
...
1111
Research
© Marigianna Skouradaki
Subgraph Isomorphism on BPMN 2.0 Process Models
BPMN 2.0 Process Models are special ...
12
Basic Concepts
1313
Research
© Marigianna Skouradaki
Exiting Attributes: Nested
1414
Research
© Marigianna Skouradaki
Exiting Attributes: Different Positions
1515
Research
© Marigianna Skouradaki
Exiting Attributes: Partially Similar
1616
Research
© Marigianna Skouradaki
Process Fragment
A Process Fragment is a piece of process model with loose
completen...
1717
Research
© Marigianna Skouradaki
Checkpoints & Relevant Process Fragments (RPFs)
 Checkpoint (the starting points)
...
1818
Research
© Marigianna Skouradaki
Checkpoints & Relevant Process Fragments
K = 2 Process ModelsCheckpoints: Events, Ga...
1919
Research
© Marigianna Skouradaki
Checkpoints & Relevant Process Fragments
K = 2 Process ModelsCheckpoints: Events, Ga...
2020
Research
© Marigianna Skouradaki
Checkpoints & Relevant Process Fragments
K = 2 Process ModelsCheckpoints: Events, Ga...
2121
Research
© Marigianna Skouradaki
Checkpoints & Relevant Process Fragments
K = 2 Process ModelsCheckpoints: Events, Ga...
2222
Research
© Marigianna Skouradaki
Checkpoints & Relevant Process Fragments
K = 2 Process ModelsCheckpoints: Events, Ga...
2323
Research
© Marigianna Skouradaki
Checkpoints & Relevant Process Fragments
K = 2 Process ModelsCheckpoints: Events, Ga...
2424
Research
© Marigianna Skouradaki
Checkpoints & Relevant Process Fragments
K = 2 Process ModelsCheckpoints: Events, Ga...
25
Algorithm
2626
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
2727
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
2828
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
2929
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3030
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3131
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3232
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3333
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3434
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3535
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3636
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3737
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3838
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
3939
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4040
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4141
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4242
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4343
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4444
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4545
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4646
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4747
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4848
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
4949
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
5050
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© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
5151
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
5252
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
5353
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
5454
Research
© Marigianna Skouradaki
Algorithm: Discovery of RPFs
K = 2 Process ModelsCheckpoints: Events, Gateways N = 3...
55
Evaluation and Validation
5656
Research
© Marigianna Skouradaki
Validation & Evaluation
 46 artificial BPMN 2.0 Process Models
 BPMN 2.0 Standard ...
5757
Research
© Marigianna Skouradaki
Validation: Process Models Used as Input
5858
Research
© Marigianna Skouradaki
Validation: Discovered RPFs
5959
Research
© Marigianna Skouradaki
Comparison Complexity:
Number of totally
compared checkpoint flows
Execution Times v...
6060
Research
© Marigianna Skouradaki
Average Execution Time vs. Average Comparison Complexity
0
5
10
15
20
25
30
35
40
45...
6161
Research
© Marigianna Skouradaki
Conclusions & Outlook
 Set the theoretical framework
 Sub-graph isomorphism on BPM...
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Application of Sub-Graph Isomorphism to Extract Reoccurring Structures from BPMN 2.0 Process Models

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The state-of-art approaches in structural similarities
of process models base their operations on behavioral
data and text semantics. These data is usually missing from
mock-up or obfuscated process models. This fact makes it
complicated to apply current approaches on these types of
models. We examine the problem of the automated detection of
re-occurring structures in a collection of process models, when
text semantics or behavioral data are missing. This problem
is a case of (sub)graph isomorphism, which is mentioned as
NP-complete in the literature. Since the process models are
very special types of attributed directed graphs we are able to
develop an approach that runs with logarithmic complexity. In
this work we set the theoretical basis, develop a configurable
approach for the detection of re-occurring structures in any
process models collection, and validate it against a set of BPMN
2.0 models. We define two execution scenarios and discuss
the relation of the execution times with the complexity of the
comparisons. Finally, we analyze the detected structures, and
propose the configurations that lead to optimal results.

==========================================

Skouradaki, Marigianna; Görlach, Katharina; Hahn, Michael; Frank, Leymann; Application of Sub-Graph Isomorphism to Extract Reoccurring Structures from BPMN 2.0 Process Models. In: Proceedings of the 9th International IEEE Symposium on Service Oriented Systems Engineering, SOSE 2015, 30 March – 3 April, 2015, San Francisco, USA

@inproceedings{SkouradakiSOSE2015,
author = {Marigianna Skouradaki and Katharina Görlach and Michael Hahn and
Frank Leymann},
title = {Application of Sub-Graph Isomorphism to Extract Reoccurring
Structures from BPMN 2.0 Process Models},
booktitle = {Proceedings of the 9th International IEEE Symposium on Service
Oriented Systems Engineering, SOSE 2015,
30 March – 3 April, 2015, San Francisco, USA},
year = {2015},
publisher = {IEEE Computer Society}
}

Published in: Engineering
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Application of Sub-Graph Isomorphism to Extract Reoccurring Structures from BPMN 2.0 Process Models

  1. 1. University of Stuttgart Universitätsstr. 38 70569 Stuttgart Germany Phone +49-711-685 88477 Fax +49-711-685 88472 Research Marigianna Skouradaki, Katharina Görlach, Michael Hahn, Frank Leymann Institute of Architecture of Application Systems {firstname.lastname}@iaas.uni-stuttgart.de Applying Subgraph Isomorphism to Extract Reoccurring Structures from BPMN 2.0 Process Models
  2. 2. 22 Research © Marigianna Skouradaki BPMN 2.0 Process Models Collection Fragments Repository Workload Mix Graph Matching Selection Criteria Composition Criteria 80% 20% Motivation: Generation of Realistic Workload
  3. 3. 33 Research © Marigianna Skouradaki Agenda  Process Model Matching  Basic Concepts  Algorithm  Evaluation & Validation  Conclusions & Outlook
  4. 4. 4 Process Matching
  5. 5. 55 Research © Marigianna Skouradaki BPMN 2.0 Collection Characteristics  Detect the reoccurring structures on BPMN 2.0 process models which:  Might be anonymized (no text information available)  Might be mock-up models (non-executable)
  6. 6. 66 Research © Marigianna Skouradaki Text Matching  Cannot be applied to anonymized models
  7. 7. 88 Research © Marigianna Skouradaki Matching Executional Information log  Comparing produced execution logs Cannot be applied on mock-up models log 2
  8. 8. 99 Research © Marigianna Skouradaki Structural Matching
  9. 9. 1010 Research © Marigianna Skouradaki The Challenge of Graph Isomorphism NonDeterministic Polynomial Time (NP – Complete) The time required to solve the problem using any currently known algorithm increases very quickly as the size of the problem grows.
  10. 10. 1111 Research © Marigianna Skouradaki Subgraph Isomorphism on BPMN 2.0 Process Models BPMN 2.0 Process Models are special types of graphs Subgraph isomorphism can be applied in lower complexity1 1 R. M Verma.; and S. W. Reyner; “An analysis of a good algorithm for the subtree problem, correlated,” SIAM J. Comput., vol. 18, no. 5, pp. 906–908, Oct. 1989.
  11. 11. 12 Basic Concepts
  12. 12. 1313 Research © Marigianna Skouradaki Exiting Attributes: Nested
  13. 13. 1414 Research © Marigianna Skouradaki Exiting Attributes: Different Positions
  14. 14. 1515 Research © Marigianna Skouradaki Exiting Attributes: Partially Similar
  15. 15. 1616 Research © Marigianna Skouradaki Process Fragment A Process Fragment is a piece of process model with loose completeness and consistency. The existence of process graph elements (start, end, activities, context etc.) is possible but not imperative in a process fragment. However, a process fragment must have at least one activity and there must be a way to convert it to an executable process graph.2 1. It is not necessarily related with a complete process model 2. A starting point is not defined 3. Existence of split or merge node is optional 2D. Schumm, F. Leymann, Z. Ma, T. Scheibler, and S. Strauch, “Integrating Compliance into Business Processes: Process Fragments as Reusable Compliance Controls” in MKWI’10, Göttingen, Germany, February 23-25, 2010, Ed., Conference Paper, pp. 2125–2137.
  16. 16. 1717 Research © Marigianna Skouradaki Checkpoints & Relevant Process Fragments (RPFs)  Checkpoint (the starting points)  A pre-configured type of node that is used as start point of the “extended” process fragments  Relevant Process Fragment  Exists in at least K business processes  Starts with a checkpoint  Has at least N nodes including the checkpoint  Contains at least one activity
  17. 17. 1818 Research © Marigianna Skouradaki Checkpoints & Relevant Process Fragments K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  18. 18. 1919 Research © Marigianna Skouradaki Checkpoints & Relevant Process Fragments K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  19. 19. 2020 Research © Marigianna Skouradaki Checkpoints & Relevant Process Fragments K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes RPF RPF
  20. 20. 2121 Research © Marigianna Skouradaki Checkpoints & Relevant Process Fragments K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  21. 21. 2222 Research © Marigianna Skouradaki Checkpoints & Relevant Process Fragments K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes RPF RPF
  22. 22. 2323 Research © Marigianna Skouradaki Checkpoints & Relevant Process Fragments K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  23. 23. 2424 Research © Marigianna Skouradaki Checkpoints & Relevant Process Fragments K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes RPF
  24. 24. 25 Algorithm
  25. 25. 2626 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  26. 26. 2727 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  27. 27. 2828 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  28. 28. 2929 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  29. 29. 3030 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  30. 30. 3131 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  31. 31. 3232 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  32. 32. 3333 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  33. 33. 3434 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  34. 34. 3535 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  35. 35. 3636 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  36. 36. 3737 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  37. 37. 3838 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  38. 38. 3939 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  39. 39. 4040 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  40. 40. 4141 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  41. 41. 4242 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  42. 42. 4343 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  43. 43. 4444 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  44. 44. 4545 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  45. 45. 4646 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  46. 46. 4747 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  47. 47. 4848 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  48. 48. 4949 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  49. 49. 5050 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  50. 50. 5151 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  51. 51. 5252 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  52. 52. 5353 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes
  53. 53. 5454 Research © Marigianna Skouradaki Algorithm: Discovery of RPFs K = 2 Process ModelsCheckpoints: Events, Gateways N = 3 Nodes …continue likewise..  Will not work for cycles
  54. 54. 55 Evaluation and Validation
  55. 55. 5656 Research © Marigianna Skouradaki Validation & Evaluation  46 artificial BPMN 2.0 Process Models  BPMN 2.0 Standard Example Processes  Models used in Pietsch and Wenzel, 2012  2070 Comparisons Scenario 1: {events, gateways} Scenario 2: {events, gateways, tasks}
  56. 56. 5757 Research © Marigianna Skouradaki Validation: Process Models Used as Input
  57. 57. 5858 Research © Marigianna Skouradaki Validation: Discovered RPFs
  58. 58. 5959 Research © Marigianna Skouradaki Comparison Complexity: Number of totally compared checkpoint flows Execution Times vs. Comparison Complexities
  59. 59. 6060 Research © Marigianna Skouradaki Average Execution Time vs. Average Comparison Complexity 0 5 10 15 20 25 30 35 40 45 0 200 400 600 AverageExecutionTimes(ms) Average Comparison Complexities Scenario 1 Scenario 2 O(n log n)
  60. 60. 6161 Research © Marigianna Skouradaki Conclusions & Outlook  Set the theoretical framework  Sub-graph isomorphism on BPMN 2.0 process models  The algorithm can run in logarithmic complexity (experimental)  Definition of checkpoints is not important for timing, but for filtering and clustering  Theoretical proof of the algorithm’s complexity  Apply filtering  Assign frequency values  Increase expressiveness of Comparison Complexity Thank you! Questions? 

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