Abstract
Model-based engineering (MBE) aims at increasing the effectiveness of engineering by using models as important artifacts in the development process. While empirical studies on the use and the effects of MBE in industry exist, only few of them target the embedded systems domain. We contribute to the body of knowledge with an empirical study on the use and the assessment of MBE in that particular domain. The goal of this study is to assess the current state-of-practice and the challenges the embedded systems domain is facing due to shortcomings with MBE. We collected quantitative data from 113 subjects, mostly professionals working with MBE, using an online survey. The collected data spans different aspects of MBE, such as the used modeling languages, tools, notations, effects of MBE introduction, or shortcomings of MBE. Our main findings are that MBE is used by a majority of all participants in the embedded systems domain, mainly for simulation, code generation, and documentation. Reported positive effects of MBE are higher quality and improved reusability. Main shortcomings are interoperability difficulties between MBE tools, high training effort for developers and usability issues. Our study offers valuable insights into the current industrial practice and can guide future research in the fields of systems modeling and embedded systems.
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Notes
Through www.soscisurvey.de.
In the following, we state only MATLAB instead of MATLAB/Simulink/Stateflow.
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Acknowledgments
The research leading to these results has received partial funding from the European Union’s Seventh Framework Program (FP7/2007-2013) for CRYSTAL-Critical System Engineering Acceleration Joint Undertaking under Grant Agreement No. 332830 and from Vinnova under DIARIENR 2012-04304. Further, the authors gratefully acknowledge financial support from FFG Austria for the project in which the above presented research results were achieved. We would also like to thank Aleksander Lodwich, Jos Langen and Leon Bouwmeester for participating in the survey design and contributing to the final study.
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Communicated by Dr. Jürgen Dingel and Wolfram Schulte.
Appendix: Key terms and definitions
Appendix: Key terms and definitions
Throughout the questionnaire, we use numerous terms and keywords. Even though most of these are common language in practice, we define what we mean by them in order to support readers who are not familiar with them. We reuse existing definitions from well-known sources where applicable.
1.1 Completeness
“The degree to which the specification contains all information which is necessary for developing a system that satisfies the stakeholders desires and needs” [12].
1.2 Consistency
“The degree of uniformity, standardization, and freedom from contradiction among the documents or parts of a system or component” [18].
1.3 Embedded systems
Embedded systems are systems that are “integral components of larger systems”, which are used to “control and/or directly monitor that system using special hardware devices” [19].
1.4 Formal methods
“Mathematically based techniques for the specification, development and verification of software and hardware systems” [14]. This definition includes more specific terms, such as formal verification.
1.5 Formal verification
“A functional verification process in which analysis of a design and a property yields a logical inference about whether the property holds for all behaviors of the design. If a property is declared true by a formal verification tool, no simulation can show it to be false. If the property does not hold for all behaviors, then the formal verification process should provide a specific counterexample to the property, if possible” [20].
1.6 Integrity
“The degree to which a system or component prevents unauthorized access to, or modification of, computer programs or data” [18].
1.7 Model
We use the following definition, based on Stachowiak’s features of a model [33]: A model is a representation of entities and relationships in the real world with a certain correspondence for a certain purpose.
1.8 Model-driven development
“Model-driven development (MDD) is a development paradigm that uses models as the primary artifact of the development process” [4].
1.9 Model-driven engineering
“Model-driven engineering (MDE) would be a superset of MDD because, as the E in MDE suggests, MDE goes beyond of the pure development activities and encompasses other model-based tasks of a complete software engineering process” [4]. This means that the term MDE encompasses all artifacts arising from the engineering process as artifacts that are possibly modeled, e.g., requirements, documentation, or designs.
1.10 Model-based engineering
The “Model-based engineering (MBE) process is a process in which software models play an important role although they are not necessarily the key artifacts of the development (i.e., they do NOT ‘drive’ the process as in MDE)” [4].
1.11 Quality
“(1) The degree to which a system, component, or process meets specified requirements. (2) The degree to which a system, component, or process meets customer or user needs or expectations” [18].
1.12 Simulation
“(1) A model that behaves or operates like a given system when provided a set of controlled inputs; (2) the process of developing or using a model as in (1)” [18].
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Liebel, G., Marko, N., Tichy, M. et al. Model-based engineering in the embedded systems domain: an industrial survey on the state-of-practice. Softw Syst Model 17, 91–113 (2018). https://doi.org/10.1007/s10270-016-0523-3
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DOI: https://doi.org/10.1007/s10270-016-0523-3