Using Heuristic Algorithms for Fast Alignment between Business Processes and Goals

Abstract

Goal modeling is widely used to align stakeholders requirements with architectural models. In contrast to goal models which are usually defined by stakeholders, architectural models are not always defined explicitly, or systems may not be used as they were designed. To understand the real behavior of a system, process mining techniques can be applied. These techniques allow us to automatically construct real models from the system's event logs. These real models can be compared to goal models to reveal their common and different parts. Unfortunately, graph-based approaches used for the model comparison are computationally expensive and can hardly be applied to large process models constructed from real-life event logs. In this paper, we adapt well-known heuristic approaches to efficiently compare process models. These approaches were tested on real data. The obtained results can be further used to compare real and expected (goal) process behavior.