A systematic approach for performance evaluation using process mining: the POSIDONIA operations case study

Modelling plays an important role in the development of software applications, in particular for the assessment of non functional requirements such as performance. The value of a model depends on the level of alignment with the reality. In this paper, we propose a systematic approach to get a performance model that is a good representation of the system under analysis. From an UML-based system design we get automatically a normative Petri net model, which formally represents the system supposed behaviour, by applying model-to-model (M2M) transformation techniques. Then, a conformance checking technique is iteratively applied to align -from the qualitative point of view- the normative model and the data log until the required fitness threshold is not reached. Finally, a trace-driven simulation technique is used to enrich the aligned model with timing specification from the data log, then obtaining the performance Generalized Stochastic Petri Net (GSPN) model. The proposed approach has been applied to a customizable Integrated Port Operations Management System, POSIDONIA Operations, where the performance model has been used to analyse the scalability of the product considering different deployment configurations.