Iskra: a tool for process model repair

This paper is dedicated to a tool whose aim is to facilitate process mining experiments and evaluation of the repair algorithms. Process mining is a scientific area which provides solutions and algorithms for discovery and analysis of business processes based on event logs. Process mining has three main areas of interest: model discovery, conformance checking and enhancement. The paper focuses exclusively on the tasks of enhancement. The goal of the enhancement process is to refine existing process models in order to make them conform to given event logs. The particular approach of enhancement, which is considered in the paper, is called decomposed model repair. It is assumed that event logs describe correct and up-to-date behavior of business processes, whereas process models may be erroneous. The proposed approach consists of several independent modules implementing different stages of the repair process. This architecture allows for more flexible repair configuration. Moreover, it allows researchers to conduct experiments with algorithms used by each module in isolation from other modules. Although the paper is devoted to the implementation part of the approach, theoretical preliminaries essential for domain understanding are provided. Moreover, a typical use case of the tool is shown as well as guides to extending the tool and enriching it with extra algorithms and functionality. Finally, other solutions which can be used for implementation of repair schemes are considered, pros and cons of using them are mentioned.