Over the last decades, the field of process mining has emerged as a response to a growing amount of event data being recorded in the context of business processes. Concurrently with the increasing amount of literature produced in this field, a set of tools has been developed to implement the various algorithms and provide them to end users. However, the majority of tools does not provide the possibility of creating workflows which can be reused at a later point in time to reproduce the results, and most tools are not easily customizable. This paper introduces bupaR, an integrated collection of Rpackages which creates a framework for reproducible process analysis in R and supports different steps of a process analysis project, from data extraction to data analysis. It is an extensible framework of several R-packages to analyse process data, each with their specific purpose and set of tools.

No abstract

Abstract:Testing and controlling business processes, activities, data and results is becoming increasingly important for companies. Based on the literature, business tests can be divided into three domains, i.e. performance, risk and compliance and separate domain-specific frameworks have been developed. These different domains and frameworks hint at some aspects that need to be taken into account when managing business tests in a company. In this paper we identify the most important concepts concerning business tests and their management and we provide a first conceptual business test model. We do this based on an archival research study in which we analyse business tests performed by an international consultancy company.