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          <dc:title>Continuous Non-Intrusive Hybrid WCET Estimation Using Waypoint Graphs</dc:title>
          <dc:creator>Dreyer, Boris</dc:creator>
          <dc:creator>Hochberger, Christian</dc:creator>
          <dc:creator>Lange, Alexander</dc:creator>
          <dc:creator>Wegener, Simon</dc:creator>
          <dc:creator>Weiss, Alexander</dc:creator>
          <dc:subject>Hybrid Worst-Case Execution Time (WCET) Estimation for Multicore Processors</dc:subject>
          <dc:subject>Real-time Systems</dc:subject>
          <dc:description>Traditionally, the Worst-Case Execution Time (WCET) of Embedded Software has been estimated using analytical approaches. This is effective, if good models of the processor/System-on-Chip (SoC) architecture exist. Unfortunately, modern high performance SoCs often contain unpredictable and/or undocumented components that influence the timing behaviour. Thus, analytical results for such processors are unrealistically pessimistic. One possible alternative approach seems to be hybrid WCET analysis, where measurement data together with an analytical approach is used to estimate worst-case behaviour. Previously, we demonstrated how continuous evaluation of basic block trace data can be used to produce detailed statistics of basic blocks in embedded software. In the meantime it has become clear that the trace data provided by modern SoCs delivers a different type of information. In this contribution, we show that even under realistic conditions, a meaningful analysis can be conducted with the trace data.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Boris Dreyer and Christian Hochberger and Alexander Lange and Simon Wegener and Alexander Weiss</dc:contributor>
          <dc:date>2016</dc:date>
          <dc:relation>Is Part Of OASIcs, Volume 55, 16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016)</dc:relation>
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          <dc:identifier>doi:10.4230/OASIcs.WCET.2016.4</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-68977</dc:identifier>
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          <dc:language>eng</dc:language>
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