What are the Problem Makers: Discovering the Most Frequently Changed Activities in Adaptive Processes

Recently, a new generation of adaptive Process-Aware Information System (PAIS) has emerged, which enables dynamic service changes (i.e., changes of instances derived from a composite service and process respectively). This, in turn, results in a large number of process variants derived from the same process model, but differing in their structure due to the applied changes. Since such process variants are expensive to maintain, the process model should evolve accordingly. It is therefore our goal to discover those activities that have been more often involved in process (instance) adaptations than others, such that we can focus on them when re-designing the process model. This paper provides two approaches to rank activities based on their involvement in process adaptations and process configurations respectively. The first approach allows to precisely rank the activities, but it is very expensive to perform since the algorithm is at $\mathcal{NP}$ level. We therefore provide as alternative approach an approximation ranking algorithm which computes in polynomial time. The performance of the approximation algorithm is evaluated and compared through a comprehensive simulation of 3600 process models. By applying statistical significance tests, we can also identify several factors which influence the performance of the approximation ranking algorithm.