Measurement-Based Probabilistic Timing Analysis (MBPTA) derives WCET estimates for tasks running on processors comprising high-performance features such as caches. MBPTA's correct application requires the system to exhibit certain timing properties, which can be achieved by injecting randomisation in the timing behaviour of the task under analysis. However, existing software-randomisation techniques require costly modifications in the industrial production toolchain (compiler, linker, runtime or hardware) in terms of development and certification. In this paper we present TASA, a new software randomisation tool that relies on source-code transformations of the application (i) requiring no changes in existing toolchains, which heavily reduces tool qualification and implementation costs; and (ii) achieving competitive WCET estimates that we assess on a gcc- and a llvm-based compilation toolchain on a real board.

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), 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 the FPU grant AP2010-4208. Jaume Abella is partially supported by the Spanish Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717.

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