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This paper describes four impact case studies where real-time systems research has been successfully transferred into industrial practice. In three cases, the technology created was translated into a viable commercial product via a start-up company. This technology transfer led to the creation and sustaining of a large number of high technology jobs over a 20 year period. The final case study involved the direct transfer of research results into an engineering company. Taken together, all four case studies have led to significant advances in automotive electronics and avionics, providing substantial returns on investment for the companies using the technology.

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., The research leading to these results has received funding from the European Community’s FP7 [FP7/2007-2013] under the PROXIMA Project (www.proxima-project.eu), grant agreement no 611085. This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717., Peer Reviewed, Postprint (author's final draft)

Timing Verification is a fundamental step in real-time embedded systems, with measurement-based timing analysis (MBTA) being the most common approach used to that end. We present a Space case study on a real platform that has been modified to support a probabilistic variant of MBTA called MBPTA. Our platform provides the properties required by MBPTA with the predicted WCET estimates with MBPTA being competitive to those with current MBTA practice while providing more solid evidence on their correctness for certification., The research leading to these results has received funding from the European Community’s FP7 [FP7/2007-2013] under the PROXIMA Project (www.proxima-project.eu), grant agreement no 611085. This work has also been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2015-65316-P and the HiPEAC Network of Excellence. Jaume Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. Carles Hernandez is jointly funded by the Spanish Ministry of Economy and Competitiveness and FEDER funds through grant TIN2014-60404-JIN., Peer Reviewed, Postprint (author's final draft)

The use of increasingly complex hardware and software platforms in response to the ever rising performance demands of modern real-time systems complicates the verification and validation of their timing behaviour, which form a time-and-effort-intensive step of system qualification or certification. In this paper we relate the current state of practice in measurement-based timing analysis, the predominant choice for industrial developers, to the proceedings of the PROXIMA (Probabilistic real-time control of mixed-criticality multicore systems) project in that very field. We recall the difficulties that the shift towards more complex computing platforms causes in that regard. Then we discuss the probabilistic approach proposed by PROXIMA to overcome some of those limitations. We present the main principles behind the PROXIMA approach as well as the changes it requires at hardware or software level underneath the application. We also present the current status of the project against its overall goals, and highlight some of the principal confidence-building results achieved so far., The research leading to these results has received funding from the European Community’s Seventh Framework Programme [FP7/2007-2013] under the PROXIMA Project (grant agreement 611085). Carles Hern´andez is jointly funded by the Spanish Ministry of Economy and Competitiveness (MINECO) and FEDER funds through grant TIN2014-60404-JIN. Jaume Abella has been partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717., Peer Reviewed, Postprint (author's final draft)

The pressing market demand for competitive performance/cost ratios compels Critical Real-Time Embedded Systems industry to employ feature-rich hardware. The ensuing rise in hardware complexity however makes worst-case execution time (WCET) analysis of software programs – which is often required, especially for programs at the highest levels of integrity – an even harder challenge. State-of-the-art WCET analysis techniques are hampered by the soaring cost and complexity of obtaining accurate knowledge of the internal operation of advanced processors and the difficulty of relating data obtained from measurement observations with reliable worst-case behaviour. This frustrating conundrum calls for novel solutions, with low intrusiveness on development practice. Measurement-Based Probabilistic Timing Analysis (MBPTA) techniques offer the opportunity to simultaneously reduce the cost of acquiring the knowledge needed for computing reliable WCET bounds and gain increased confidence in the representativeness of measurement observations. This paper describes the changes required in the design of several high-performance features – massively used in modern processors – to meet MBPTA requirements. © 2016 Elsevier B.V.

The pressing market demand for competitive performance/cost ratios compels Critical Real-Time Embedded Systems industry to employ feature-rich hardware. The ensuing rise in hardware complexity however makes worst-case execution time (WCET) analysis of software programs - which is often required, especially for programs at the highest levels of integrity - an even harder challenge. State-of-the-art WCET analysis techniques are hampered by the soaring cost and complexity of obtaining accurate knowledge of the internal operation of advanced processors and the difficulty of relating data obtained from measurement observations with reliable worst-case behaviour. This frustrating conundrum calls for novel solutions, with low intrusiveness on development practice. Measurement-Based Probabilistic Timing Analysis (MBPTA) techniques offer the opportunity to simultaneously reduce the cost of acquiring the knowledge needed for computing reliable WCET bounds and gain increased confidence in the representativeness of measurement observations. This paper describes the changes required in the design of several high-performance features - massively used in modern processors - to meet MBPTA requirements., This work has received funding from the European Community's Seventh 1025 Framework Programme [FP7/2007-2013] under grant agreement 611085 (PROXIMA, www.proxima-project.eu). Support was also provided by the Ministry of Science and Technology of Spain under contract TIN2015-65316-P and the HiPEAC Network of Excellence. Leonidas Kosmidis is funded by the Spanish Ministry of Education under FPU grant AP2010-4208. Jaume Abella has been 1030 partially supported by the MINECO under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717. The authors wish to acknowledge Michael Houston, Liliana Cucu-Grosjean and Luca Santinelli for contributing to the genesis of this work., Peer Reviewed, Postprint (author's final draft)