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Documents authored by Hellinckx, Peter

Document
DOI: 10.4230/OASIcs.WCET.2018.5
A New Hybrid Approach on WCET Analysis for Real-Time Systems Using Machine Learning

Authors: Thomas Huybrechts, Siegfried Mercelis, and Peter Hellinckx

Published in: OASIcs, Volume 63, 18th International Workshop on Worst-Case Execution Time Analysis (WCET 2018)

Abstract
The notion of the Worst-Case Execution Time (WCET) allows system engineers to create safe real-time systems. This value is used to schedule all software tasks before their deadlines. Failing these deadlines will cause catastrophic events, e.g. vehicle crashes, failing to detect dangerous anomalies, etc. Different analysis methodologies exist to determine the WCET. However, these methods do not provide early insight in the WCET during development. Therefore, pessimistic assumptions are made by system designers resulting in more expensive, overqualified hardware. In this paper, an extension on the hybrid methodology is proposed which implements a predictor model using Machine Learning (ML). This new approach estimates the WCET on smaller entities of the code, so-called hybrid blocks, based on software and hardware features. As a result, the ML-based hybrid analysis provides insight of the WCET early-on in the development process and refines its estimate when more detailed features are available. In order to facilitate the extraction of code-related features, a new tool for the COBRA framework is proposed. This paper proves the potential of the ML-based hybrid approach by conducting multiple experiments based on the TACLeBench on a first prototype. A set of annotated code features were used to train and validate eight different regression models. The results already show promising estimates without tuning any hyperparameters, proving the potential of the methodology.
Cite as

Thomas Huybrechts, Siegfried Mercelis, and Peter Hellinckx. A New Hybrid Approach on WCET Analysis for Real-Time Systems Using Machine Learning. In 18th International Workshop on Worst-Case Execution Time Analysis (WCET 2018). Open Access Series in Informatics (OASIcs), Volume 63, pp. 5:1-5:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{huybrechts_et_al:OASIcs.WCET.2018.5,
  author =	{Huybrechts, Thomas and Mercelis, Siegfried and Hellinckx, Peter},
  title =	{{A New Hybrid Approach on WCET Analysis for Real-Time Systems Using Machine Learning}},
  booktitle =	{18th International Workshop on Worst-Case Execution Time Analysis (WCET 2018)},
  pages =	{5:1--5:12},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-073-6},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{63},
  editor =	{Brandner, Florian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2018.5},
  URN =		{urn:nbn:de:0030-drops-97510},
  doi =		{10.4230/OASIcs.WCET.2018.5},
  annote =	{Keywords: Worst-Case Execution Time, Machine Learning, Hybrid Analysis, Feature Selection, COde Behaviour fRamework}
}
Document
DOI: 10.4230/OASIcs.WCET.2016.2
TACLeBench: A Benchmark Collection to Support Worst-Case Execution Time Research

Authors: Heiko Falk, Sebastian Altmeyer, Peter Hellinckx, Björn Lisper, Wolfgang Puffitsch, Christine Rochange, Martin Schoeberl, Rasmus Bo Sørensen, Peter Wägemann, and Simon Wegener

Published in: OASIcs, Volume 55, 16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016)

Abstract
Engineering related research, such as research on worst-case execution time, uses experimentation to evaluate ideas. For these experiments we need example programs. Furthermore, to make the research experimentation repeatable those programs shall be made publicly available. We collected open-source programs, adapted them to a common coding style, and provide the collection in open-source. The benchmark collection is called TACLeBench and is available from GitHub in version 1.9 at the publication date of this paper. One of the main features of TACLeBench is that all programs are self-contained without any dependencies on standard libraries or an operating system.
Cite as

Heiko Falk, Sebastian Altmeyer, Peter Hellinckx, Björn Lisper, Wolfgang Puffitsch, Christine Rochange, Martin Schoeberl, Rasmus Bo Sørensen, Peter Wägemann, and Simon Wegener. TACLeBench: A Benchmark Collection to Support Worst-Case Execution Time Research. In 16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016). Open Access Series in Informatics (OASIcs), Volume 55, pp. 2:1-2:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{falk_et_al:OASIcs.WCET.2016.2,
  author =	{Falk, Heiko and Altmeyer, Sebastian and Hellinckx, Peter and Lisper, Bj\"{o}rn and Puffitsch, Wolfgang and Rochange, Christine and Schoeberl, Martin and S{\o}rensen, Rasmus Bo and W\"{a}gemann, Peter and Wegener, Simon},
  title =	{{TACLeBench: A Benchmark Collection to Support Worst-Case Execution Time Research}},
  booktitle =	{16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016)},
  pages =	{2:1--2:10},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-025-5},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{55},
  editor =	{Schoeberl, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2016.2},
  URN =		{urn:nbn:de:0030-drops-68958},
  doi =		{10.4230/OASIcs.WCET.2016.2},
  annote =	{Keywords: Benchmark, WCET analysis, real-time systems}
}
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