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Dynamic software randomisation: Lessons learnec from an aerospace case study

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10.23919/DATE.2017.7926966
 
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hdl:2117/104579

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Cros, Fabrice
Kosmidis, LeonidasMés informació
Wartel, Franck
Morales, David
Abella Ferrer, JaumeMés informació
Broster, Ian
Cazorla, Francisco J.
Document typeConference lecture
Defense date2017-05-15
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectRYC-2013-14717 (MINECO-RYC-2013-14717)
COMPUTACION DE ALTAS PRESTACIONES VII (MINECO-TIN2015-65316-P)
Abstract
Timing Validation and Verification (V&V) is an important step in real-time system design, in which a system's timing behaviour is assessed via Worst Case Execution Time (WCET) estimation and scheduling analysis. For WCET estimation, measurement-based timing analysis (MBTA) techniques are widely-used and well-established in industrial environments. However, the advent of complex processors makes it more difficult for the user to provide evidence that the software is tested under stress conditions representative of those at system operation. Measurement-Based Probabilistic Timing Analysis (MBPTA) is a variant of MBTA followed by the PROXIMA European Project that facilitates formulating this representativeness argument. MBPTA requires certain properties to be applicable, which can be obtained by selectively injecting randomisation in platform's timing behaviour via hardware or software means. In this paper, we assess the effectiveness of the PROXIMA's dynamic software randomisation (DSR) with a space industrial case study executed on a real unmodified hardware platform and an industrial operating system. We present the challenges faced in its development, in order to achieve MBPTA compliance and the lessons learned from this process. Our results, obtained using a commercial timing analysis tool, indicate that DSR does not impact the average performance of the application, while it enables the use of MBPTA. This results in tighter pWCET estimates compared to current industrial practice.
CitationCros, F. [et al.]. Dynamic software randomisation: Lessons learnec from an aerospace case study. A: "2017 Design, Automation & Test in Europe Conference & Exhibition (DATE)". 2017, p. 103-108. 
URIhttp://hdl.handle.net/2117/104579
DOI10.23919/DATE.2017.7926966
ISBN978-3-9815370-8-6
Publisher versionhttp://ieeexplore.ieee.org/document/7926966/
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  • Computer Sciences - Ponències/Comunicacions de congressos [489]
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