Abstract
Several studies report that the use of model-centric methods in the automotive domain is widespread and offers several benefits. However, existing work indicates that few modelling frameworks explicitly include requirements engineering (RE), and that natural language descriptions are still the status quo in RE. Therefore, we aim to increase the understanding of current and potential future use of models in RE, with respect to the automotive domain. In this paper, we report our findings from a multiple-case study with two automotive companies, collecting interview data from 14 practitioners. Our results show that models are used for a variety of different purposes during RE in the automotive domain, e.g. to improve communication and to handle complexity. However, these models are often used in an unsystematic fashion and restricted to few experts. A more widespread use of models is prevented by various challenges, most of which align with existing work on model use in a general sense. Furthermore, our results indicate that there are many potential benefits associated with future use of models during RE. Interestingly, existing research does not align well with several of the proposed use cases, e.g. restricting the use of models to informal notations for communication purposes. Based on our findings, we recommend a stronger focus on informal modelling and on using models for multi-disciplinary environments. Additionally, we see the need for future work in the area of model use, i.e. information extraction from models by non-expert modellers.
Highlights
Empirical evidence suggests that Model-Based Engineering (MBE) offers benefits such as quality and productivity improvements [4,40]
In this paper we investigate empirically in the automotive domain how models are already used during requirements engineering (RE), what potential practitioners see in the use of models during RE, and which roadblocks exist in this area
The User Requirements Specification (URS) is analysed in the company by the customer relations unit and a System Requirements Specification (SRS) is elicited to meet the URS requirements
Summary
Empirical evidence suggests that Model-Based Engineering (MBE) offers benefits such as quality and productivity improvements [4,40]. Negative aspects such as insufficient tool support [4,40,41] and the use of MBE with legacy software [28,40] are reported. Research regarding the state of practice of MBE has targeted the entire software engineering cycle, from requirements engineering (RE) to software development and testing, both in terms of quantitative studies [1,18,27,28,30,31,51] and qualitative studies [4,26,29,41,56] These studies typically do not investigate in detail how models are used in the respective phases of software and systems engineering. Loniewski et al [33] point out that only few model-driven approaches explicitly include RE
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