Addressing the need for strict meta-modeling in practice - a case study of AUTOSAR

Abstract

Meta-modeling has been a topic of interest in the modeling community for many years, yielding substantial number of papers describing its theoretical concepts. Many of them are aiming to solve the problem of traditional UML based domain-specific meta-modeling related to its non-compliance to the strict meta-modeling principle, such as the deep meta-modeling approach. In this paper, we show the practical use of meta-models in the automotive development process based on AUTOSAR and visualize places in the AUTOSAR meta-model which are broken according to the strict meta-modeling principle. We then explain how the AUTOSAR meta-modeling environment can be re-worked in order to comply to this principle by applying three individual approaches, each one combined with the concept of Orthogonal Classification Architecture: UML extension, prototypical pattern and deep instantiation. Finally we discuss the applicability of these approaches in practice and contrast the identified issues with the actual problems faced by the automotive meta-modeling practitioners. Our objective is to bridge the current gap between the theoretical and practical concerns in meta-modeling.