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Documents authored by Claraz, Denis

Document
DOI: 10.4230/OASIcs.WCET.2017.5
Early WCET Prediction Using Machine Learning

Authors: Armelle Bonenfant, Denis Claraz, Marianne de Michiel, and Pascal Sotin

Published in: OASIcs, Volume 57, 17th International Workshop on Worst-Case Execution Time Analysis (WCET 2017)

Abstract
For delivering a precise Worst Case Execution Time (WCET), the WCET static analysers need the executable program and the target architecture. However, a prediction (even coarse) of the future WCET would be helpful at design stages where only the source code is available. We investigate the possibility of creating predictors of the WCET based on the C source code using machine-learning (work in progress). If successful, our proposal would offer to the designer precious information on the WCET of a piece of code at the early stages of the development process.
Cite as

Armelle Bonenfant, Denis Claraz, Marianne de Michiel, and Pascal Sotin. Early WCET Prediction Using Machine Learning. In 17th International Workshop on Worst-Case Execution Time Analysis (WCET 2017). Open Access Series in Informatics (OASIcs), Volume 57, pp. 5:1-5:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{bonenfant_et_al:OASIcs.WCET.2017.5,
  author =	{Bonenfant, Armelle and Claraz, Denis and de Michiel, Marianne and Sotin, Pascal},
  title =	{{Early WCET Prediction Using Machine Learning}},
  booktitle =	{17th International Workshop on Worst-Case Execution Time Analysis (WCET 2017)},
  pages =	{5:1--5:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-057-6},
  ISSN =	{2190-6807},
  year =	{2017},
  volume =	{57},
  editor =	{Reineke, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2017.5},
  URN =		{urn:nbn:de:0030-drops-73073},
  doi =		{10.4230/OASIcs.WCET.2017.5},
  annote =	{Keywords: Early WCET, Machine Learning, Static Analysis, C Language}
}
Document
DOI: 10.4230/OASIcs.WCET.2017.9
The W-SEPT Project: Towards Semantic-Aware WCET Estimation

Authors: Claire Maiza, Pascal Raymond, Catherine Parent-Vigouroux, Armelle Bonenfant, Fabienne Carrier, Hugues Cassé, Philippe Cuenot, Denis Claraz, Nicolas Halbwachs, Erwan Jahier, Hanbing Li, Marianne de Michiel, Vincent Mussot, Isabelle Puaut, Christine Rochange, Erven Rohou, Jordy Ruiz, Pascal Sotin, and Wei-Tsun Sun

Published in: OASIcs, Volume 57, 17th International Workshop on Worst-Case Execution Time Analysis (WCET 2017)

Abstract
Critical embedded systems are generally composed of repetitive tasks that must meet hard timing constraints, such as termination deadlines. Providing an upper bound of the worst-case execution time (WCET) of such tasks at design time is necessary to guarantee the correctness of the system. In static WCET analysis, a main source of over-approximation comes from the complexity of the modern hardware platforms: their timing behavior tends to become more unpredictable because of features like caches, pipeline, branch prediction, etc. Another source of over-approximation comes from the software itself: WCET analysis may consider potential worst-cases executions that are actually infeasible, because of the semantics of the program or because they correspond to unrealistic inputs. The W-SEPT project, for "WCET, Semantics, Precision and Traceability", has been carried out to study and exploit the influence of program semantics on the WCET estimation. This paper presents the results of this project : a semantic-aware WCET estimation workflow for high-level designed systems.
Cite as

Claire Maiza, Pascal Raymond, Catherine Parent-Vigouroux, Armelle Bonenfant, Fabienne Carrier, Hugues Cassé, Philippe Cuenot, Denis Claraz, Nicolas Halbwachs, Erwan Jahier, Hanbing Li, Marianne de Michiel, Vincent Mussot, Isabelle Puaut, Christine Rochange, Erven Rohou, Jordy Ruiz, Pascal Sotin, and Wei-Tsun Sun. The W-SEPT Project: Towards Semantic-Aware WCET Estimation. In 17th International Workshop on Worst-Case Execution Time Analysis (WCET 2017). Open Access Series in Informatics (OASIcs), Volume 57, pp. 9:1-9:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{maiza_et_al:OASIcs.WCET.2017.9,
  author =	{Maiza, Claire and Raymond, Pascal and Parent-Vigouroux, Catherine and Bonenfant, Armelle and Carrier, Fabienne and Cass\'{e}, Hugues and Cuenot, Philippe and Claraz, Denis and Halbwachs, Nicolas and Jahier, Erwan and Li, Hanbing and de Michiel, Marianne and Mussot, Vincent and Puaut, Isabelle and Rochange, Christine and Rohou, Erven and Ruiz, Jordy and Sotin, Pascal and Sun, Wei-Tsun},
  title =	{{The W-SEPT Project: Towards Semantic-Aware WCET Estimation}},
  booktitle =	{17th International Workshop on Worst-Case Execution Time Analysis (WCET 2017)},
  pages =	{9:1--9:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-057-6},
  ISSN =	{2190-6807},
  year =	{2017},
  volume =	{57},
  editor =	{Reineke, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2017.9},
  URN =		{urn:nbn:de:0030-drops-73097},
  doi =		{10.4230/OASIcs.WCET.2017.9},
  annote =	{Keywords: Worst-case execution time analysis, Static analysis, Program analysis}
}
Document
DOI: 10.4230/OASIcs.WCET.2014.93
Identifying Relevant Parameters to Improve WCET Analysis

Authors: Jakob Zwirchmayr, Pascal Sotin, Armelle Bonenfant, Denis Claraz, and Philippe Cuenot

Published in: OASIcs, Volume 39, 14th International Workshop on Worst-Case Execution Time Analysis (2014)

Abstract
Highly-configurable systems usually depend on a large number of parameters imposed by both hardware and software configuration. Due to the pessimistic assumptions of WCET analysis, if left unspecified, they deteriorate the quality of WCET analysis. In such a case, supplying the WCET analyzer with additional information about parameters (a scenario), e.g. possible variable ranges or values, allows reducing WCET over-estimation, either by improving the estimate, or by validating the initial estimate for a specific configuration or mode of execution. Nevertheless, exhaustively specifying constraints on all parameters is usually infeasible and identifying relevant ones (i.e. those impacting the WCET) is difficult. To address this issue, we propose the branching statement analysis, which uses a source-based heuristic to compute branch weights and that aims at listing unbalanced conditionals that correspond to system parameters. The goal is to help system-experts identify and formulate concise scenarios about modes or configurations that have a positive impact on the quality of the WCET analysis.
Cite as

Jakob Zwirchmayr, Pascal Sotin, Armelle Bonenfant, Denis Claraz, and Philippe Cuenot. Identifying Relevant Parameters to Improve WCET Analysis. In 14th International Workshop on Worst-Case Execution Time Analysis. Open Access Series in Informatics (OASIcs), Volume 39, pp. 93-102, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{zwirchmayr_et_al:OASIcs.WCET.2014.93,
  author =	{Zwirchmayr, Jakob and Sotin, Pascal and Bonenfant, Armelle and Claraz, Denis and Cuenot, Philippe},
  title =	{{Identifying Relevant Parameters to Improve WCET Analysis}},
  booktitle =	{14th International Workshop on Worst-Case Execution Time Analysis},
  pages =	{93--102},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-69-9},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{39},
  editor =	{Falk, Heiko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2014.93},
  URN =		{urn:nbn:de:0030-drops-46085},
  doi =		{10.4230/OASIcs.WCET.2014.93},
  annote =	{Keywords: WCET Accuracy, Modes and Configuration, Flow Facts, Scenario Specification}
}
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