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Measurement-Based Probabilistic Timing Analysis: Lessons from an Integrated-Modular Avionics Case Study

Identifieur interne : 001155 ( Main/Exploration ); précédent : 001154; suivant : 001156

Measurement-Based Probabilistic Timing Analysis: Lessons from an Integrated-Modular Avionics Case Study

Auteurs : Franck Wartel [France] ; Leonidas Kosmidis [Espagne] ; Benoit Triquet [France] ; Eduardo Quinones [Espagne] ; Jaume Abella [Espagne] ; Adriana Geanina Gogonel [France] ; Andreea Baldovin [Italie] ; Enrico Mezzetti [Italie] ; Liliana Cucu-Grosjean [France] ; Tullio Vardanega [Italie] ; Francisco J. Cazorla [Espagne]

Source :

RBID : Hal:hal-00920538

Abstract

Probabilistic Timing Analysis (PTA) in general and its measurement-based variant called MBPTA in particular can mitigate some of the problems that impair current worst-case execution time (WCET) analysis techniques. MBPTA computes tight WCET bounds expressed as probabilistic exceedance functions, without needing much information on the hardware and software internals of the system. Classic WCET analysis has information needs that may be costly and difficult to satisfy, and their omission increases pessimism. Previous work has shown that MBPTA does well with benchmark programs. Real-world applications however place more demanding requirements on timing analysis than simple benchmarks. It is interesting to see how PTA responds to them. This paper discusses the application of MBPTA to a real avionics system and presents lessons learned in that process.

Url:
DOI: 10.1109/SIES.2013.6601497


Affiliations:


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<div type="abstract" xml:lang="en">Probabilistic Timing Analysis (PTA) in general and its measurement-based variant called MBPTA in particular can mitigate some of the problems that impair current worst-case execution time (WCET) analysis techniques. MBPTA computes tight WCET bounds expressed as probabilistic exceedance functions, without needing much information on the hardware and software internals of the system. Classic WCET analysis has information needs that may be costly and difficult to satisfy, and their omission increases pessimism. Previous work has shown that MBPTA does well with benchmark programs. Real-world applications however place more demanding requirements on timing analysis than simple benchmarks. It is interesting to see how PTA responds to them. This paper discusses the application of MBPTA to a real avionics system and presents lessons learned in that process.</div>
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