Process model fragmentization, clustering and merging: An empirical study

Abstract

Nowadays, it is common for an organization tomaintain thousands of business processes. Technologies that provide automatic management for such amount of models are required. The objective of this paper is to deal with the problem of process model fragmentization, clustering and merging for the consolidation of Office Automation (OA) systems in ChinaMobile Communications Corporation (CMCC). After investigating the structural statistics of real-life process model samples, we propose an approach, based on the refined process structure tree (RPST) and software product line (SPL), to automatically identify reusable process fragments and merge similar ones into master fragments. These fragments can, for example, be used to facilitate the (re)design of numerous process models. Special attention is paid to the empirical study and statistics from the experiment on a sample set of 37 real-life OA processes. Lesson learned and problems to be further considered are also proposed. © Springer International Publishing Switzerland 2014.