Stepwise structural verification of cyclic workflow models with acyclic decomposition and reduction of loops

Choi, Yongsun; Kongsuwan, Pauline; Joo, Cheol Min; Zhao, Jing

doi:10.1016/j.datak.2014.11.003

Cited by 8 publications

(10 citation statements)

References 49 publications

(132 reference statements)

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“…If behavioral relations are to be searched in cycles that lie in process components, for example, our theory does not currently work. But it should be possible to decompose cyclic process components into acyclic ones without losing behavioral relationships [27]. This is within the scope of our future work.…”

Section: Discussionmentioning

confidence: 99%

“…To evaluate PBR, we implemented it as a plugin of gPro-Analyzer [27] developed in C# (available at: https://github. com/ngoclongha/PBR.git).…”

Section: Discussionmentioning

confidence: 99%

“…In addition, it makes the structure of the model more explicit, in a less dense and more readable form. It provides also better visualization and understanding of the process model [27]. Furthermore, it is possible to replace each process component with a single node.…”

Section: B Process Components and An Extension Of Process Modelsmentioning

confidence: 99%

“…In addition, related studies propose to use structural decomposition for process models [23]. The RPST has been used for process model verification [27], [31], automated discovery of process models from event logs [32], and process model refactoring [33], among other applications.…”

Section: Related Workmentioning

confidence: 99%

“…We used gProAnalyzer [27] to filter out all pointless, syntactically incorrect, cyclic, or unsound models. During this process, semantic correction was required for each model with a newly added OR-split as Start to ensure correct behaviors [43], [44].…”

Section: A Datasetsmentioning

confidence: 99%

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Partitioning Behavioral Retrieval: An Efficient Computational Approach With Transitive Rules

Prinz

2021

IEEE Access

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The number of process models in process repositories has grown in recent years. For this reason, it is becoming increasingly important to efficiently retrieve process models from the repositories for management purposes. In fact, the method of retrieval is also essential to increase the potential of additional analysis such as similarity and behavioral analysis and compliance checking. Most retrieval methods can be classified as structural or behavioral retrieval. Behavioral retrieval considers the relationships between activities during process execution. In this paper, we introduce such a new behavior-based retrieval method called Partitioning Behavioral Retrieval. It is the first retrieval method that allows process models to contain inclusive (OR) gateways. The method is based on the dominance relation and a node-based process structure tree known from compiler theory. Although it uses instance subgraph checking as a computational basis, it derives new behavioral relations by using transitive rules. Currently, the method is limited to acyclic process models for ease of introduction. Experiments show the time advantage offered by our new method.

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Section: Discussionmentioning

confidence: 99%

“…To evaluate PBR, we implemented it as a plugin of gPro-Analyzer [27] developed in C# (available at: https://github. com/ngoclongha/PBR.git).…”

Section: Discussionmentioning

confidence: 99%

Section: B Process Components and An Extension Of Process Modelsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: A Datasetsmentioning

confidence: 99%

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Partitioning Behavioral Retrieval: An Efficient Computational Approach With Transitive Rules

Prinz

2021

IEEE Access

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Understanding and Decomposing Control-Flow Loops in Business Process Models

Prinz

Choi

2022

Lecture Notes in Computer Science

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Unraveling Iterative Control Structures from Business Processes

Si¹,

Yung²

2021

J. Comput. Sci. Technol.

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Iterative control structures allow the repeated execution of tasks, activities or sub-processes according to the given conditions in a process model. Iterative control structures can significantly increase the risk of triggering temporal exceptions since activities within the scope of these control structures could be repeatedly executed until a predefined condition is met. In this paper, we propose two approaches to unravel iterative control structures from process models. The first approach unravels loops based on zero-one principle. The second approach unravels loops based on branching probabilities assigned at split gateways. The proposed methods can be used to unfold structured loops, nested loops and crossing loops. Since the unfolded model does not contain any iterative control structures, it can be used for further analysis by process designers during the modeling phase. The proposed methods are implemented based on workflow graphs, and therefore they are compatible with modeling languages such as Business Process Modelling Notation (BPMN). In the experiments, the execution behavior of unfolded process models is compared against the original models based on the concept of runs. Experimental results reveal that runs generated from the original models can be correctly executed in the unfolded BPMN models that do not contain any loops.

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Stepwise structural verification of cyclic workflow models with acyclic decomposition and reduction of loops

Cited by 8 publications

References 49 publications

Partitioning Behavioral Retrieval: An Efficient Computational Approach With Transitive Rules

Partitioning Behavioral Retrieval: An Efficient Computational Approach With Transitive Rules

Understanding and Decomposing Control-Flow Loops in Business Process Models

Unraveling Iterative Control Structures from Business Processes

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