Application of Sub-Graph Isomorphism to Extract Reoccurring Structures from BPMN 2.0 Process Models

University of Stuttgart Universitätsstr. 38 70569 Stuttgart Germany

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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

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© 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

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Agenda

Process Model Matching

Basic Concepts

Algorithm

Evaluation & Validation

Conclusions & Outlook

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Process Matching

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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)

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Text Matching

Cannot be applied to anonymized models

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Matching Executional Information

log

Comparing produced execution logs

Cannot be applied on mock-up models

log

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Structural Matching

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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.

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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.

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Basic Concepts

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Exiting Attributes: Nested

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Exiting Attributes: Different Positions

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Exiting Attributes: Partially Similar

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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.

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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

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Checkpoints & Relevant Process Fragments

K = 2 Process Models Checkpoints: Events, Gateways N = 3 Nodes

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RPF

RPF

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RPF

RPF

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RPF

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Algorithm

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Algorithm: Discovery of RPFs


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…continue likewise..

Will not work for cycles

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Evaluation and Validation

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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}

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Validation: Process Models Used as Input

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Validation: Discovered RPFs

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Comparison Complexity:

Number of totally

compared checkpoint flows

Execution Times vs. Comparison Complexities

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Average Execution Time vs. Average Comparison Complexity

0

5

10

15

20

25

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0 200 400 600

Avera

ge E

xec

uti

on

Tim

es (

ms

)

Average Comparison Complexities

Scenario 1

Scenario 2

O(n log n)

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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?

Application of Sub-Graph Isomorphism to Extract Reoccurring Structures from BPMN 2.0 Process Models

Engineering

process models bpmn

executable process graph

complete process model

piece of process model

anonymized models

reoccurring structures

good algorithm

known algorithm