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Clone detection for business process models.

Mahdi Saeedi Nikoo1, Önder Babur1,2, Mark van den Brand1

  • 1Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands.

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|September 12, 2022
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Summary
This summary is machine-generated.

This study enhances the Statistical Analysis of Models (SAMOS) framework for detecting similar business process models. Our extended SAMOS offers improved recall in clone detection, aiding repository management.

Keywords:
Business process modelsClusteringModel analyticsModel clone detectionModel-driven engineeringRepository miningSoftware maintenanceVector space model

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Area of Science:

  • Software Engineering
  • Model-Driven Software Engineering
  • Business Process Management

Background:

  • Growing repositories of business process models increase management costs.
  • Model clone detection identifies similar fragments, benefiting repository management and refactoring.
  • Existing tools may have limitations in comprehensive model similarity analysis.

Purpose of the Study:

  • Extend the Statistical Analysis of Models (SAMOS) framework for business process model clone detection.
  • Evaluate the effectiveness of the extended SAMOS framework against existing tools.
  • Demonstrate the framework's capabilities in handling different model scoping styles.

Main Methods:

  • Extension of the Statistical Analysis of Models (SAMOS) framework.
  • Utilizing underlying techniques for model analytics and clone detection.
  • Experimental evaluations involving synthetic datasets and the SAP Reference Model Collection.

Main Results:

  • SAMOS demonstrated superior coverage of metrics in pairwise model similarity compared to Apromore.
  • SAMOS achieved higher recall in model clone detection, while Apromore showed better precision.
  • The extended SAMOS framework supports diverse model scoping styles.

Conclusions:

  • The extended SAMOS framework is effective for business process model clone detection.
  • SAMOS offers a valuable alternative for managing and analyzing large model repositories.
  • Further research can explore additional analytics and scoping options within the SAMOS framework.