Over the last few years, considerable interest has arisen in measurement-based probabilistic timing analysis. The term MBPTA has been used to indistinctly refer to a variety of different applications of Extreme Value Theory (EVT) to the timing analysis problem. The successful application of MBPTA techniques to a score of case studies has not fully dispelled the concerns that industrial stakeholders had with the quality of the computed bounds, hence ultimately with their industrial viability. Placing focus on the MBPTA methods and techniques developed in the PROARTIS and PROXIMA projects, collectively referred to as proMBPTA, we discuss the main misconceptions and pitfalls that can prevent a sound application of EVT-based WCET analysis. Using a combination of arguments and support examples, we show that proMBPTA is a rigorous process, fully amenable to sound and sustainable industrial use.

On uses of extreme value theory fit for industrial-quality WCET analysis

Vardanega, Tullio
Supervision
;
2017

Abstract

Over the last few years, considerable interest has arisen in measurement-based probabilistic timing analysis. The term MBPTA has been used to indistinctly refer to a variety of different applications of Extreme Value Theory (EVT) to the timing analysis problem. The successful application of MBPTA techniques to a score of case studies has not fully dispelled the concerns that industrial stakeholders had with the quality of the computed bounds, hence ultimately with their industrial viability. Placing focus on the MBPTA methods and techniques developed in the PROARTIS and PROXIMA projects, collectively referred to as proMBPTA, we discuss the main misconceptions and pitfalls that can prevent a sound application of EVT-based WCET analysis. Using a combination of arguments and support examples, we show that proMBPTA is a rigorous process, fully amenable to sound and sustainable industrial use.
2017
2017 12th IEEE International Symposium on Industrial Embedded Systems, SIES 2017 - Proceedings
12th IEEE International Symposium on Industrial Embedded Systems, SIES 2017
9781538631669
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3257896
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