Skip to main content

Mining version histories for change impact analysis in business process model repositories

Journal Article


Abstract


  • In order to remain competitive and sustainable in today's ever-changing business environments, organizations need to frequently make changes to their business activities and the corresponding business process models. One of the critical issues that an organization faces is change impact analysis: estimating the potential effects of changing a business process to other processes in the organization's business process repository. In this paper, we propose an approach to change impact analysis which mines a version history of a business process model repository. Our approach then identifies business process models that have been co-changed in the past and uses this knowledge to predict the impact of future changes. An empirical validation on a real business process model repository has showed the effectiveness of our approach in predicting impact of a change.

Publication Date


  • 2015

Citation


  • Dam, H. Khanh. & Ghose, A. (2015). Mining version histories for change impact analysis in business process model repositories. Computers in Industry, 67 72-85. Computers in Industry

Scopus Eid


  • 2-s2.0-84920772164

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5031

Has Global Citation Frequency


Number Of Pages


  • 13

Start Page


  • 72

End Page


  • 85

Volume


  • 67

Place Of Publication


  • Netherlands

Abstract


  • In order to remain competitive and sustainable in today's ever-changing business environments, organizations need to frequently make changes to their business activities and the corresponding business process models. One of the critical issues that an organization faces is change impact analysis: estimating the potential effects of changing a business process to other processes in the organization's business process repository. In this paper, we propose an approach to change impact analysis which mines a version history of a business process model repository. Our approach then identifies business process models that have been co-changed in the past and uses this knowledge to predict the impact of future changes. An empirical validation on a real business process model repository has showed the effectiveness of our approach in predicting impact of a change.

Publication Date


  • 2015

Citation


  • Dam, H. Khanh. & Ghose, A. (2015). Mining version histories for change impact analysis in business process model repositories. Computers in Industry, 67 72-85. Computers in Industry

Scopus Eid


  • 2-s2.0-84920772164

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5031

Has Global Citation Frequency


Number Of Pages


  • 13

Start Page


  • 72

End Page


  • 85

Volume


  • 67

Place Of Publication


  • Netherlands