Abstract
In our mission to advance innovation by industrial adoption of academic results, we perform many projects with high-tech industries. Favoring formal methods, we observe a gap between industrial needs in performance modeling and the analysis capabilities of formal methods for this goal. After clarifying this gap, we highlight some relevant deficiencies for state-of-the-art quantitative analysis techniques (focusing on model checking and simulation). As an ingredient to bridging the gap, we propose to unite domain-specific industrial contexts with academic performance approaches through Domain Specific Languages (DSLs). We illustrate our vision with examples from different high-tech industries and discuss lessons learned from the migration process of adopting it.
This work was supported by the ARTEMIS Joint Undertaking through the Crystal project on Critical System Engineering Acceleration and the Dutch program COMMIT through the Allegio project on Composable Embedded Systems for Healthcare.
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Notes
- 1.
Notice that the terms component and system are relative to the level of detail at which the design takes place where the highest level denotes complete products and the lowest level comprises automatically synthesizable or bought off-the-shelf parts.
- 2.
The sheer size of systems (in the number of parts) is a different kind of complexity.
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Theelen, B., Hooman, J. (2015). Uniting Academic Achievements on Performance Analysis with Industrial Needs. In: Campos, J., Haverkort, B. (eds) Quantitative Evaluation of Systems. QEST 2015. Lecture Notes in Computer Science(), vol 9259. Springer, Cham. https://doi.org/10.1007/978-3-319-22264-6_1
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