A. Hamann, D. Ziegenbein, S. Kramer, M. Lukasiewycz
{"title":"Demo Abstract: Demonstration of the FMTV 2016 Timing Verification Challenge","authors":"A. Hamann, D. Ziegenbein, S. Kramer, M. Lukasiewycz","doi":"10.1109/RTAS.2016.7461330","DOIUrl":null,"url":null,"abstract":"The complex dynamic behavior of automotive software systems, in particular engine management, in combination with emerging multi-core execution platforms, significantly increased the problem space for timing analysis methods. As a result, the risk of divergence between academic research and industrial practice is currently increasing. Therefore, we provided a concrete automotive benchmark for the Formal Methods for Timing Verification (FMTV) challenge 2016 (https://waters2016.inria.fr/challenge/), a full blown performance model of a modern engine management system (downloadable at http://ecrts.eit.uni-kl.de/forum/viewtopic.php?f=27&t=62), with the goal to challenge existing timing analysis approaches with respect to their expressiveness and precision. In the demo session we will present the performance model of the engine management system using the Amalthea tool (http://www.amalthea-project.org/). Furthermore, we will show the model in action using professional timing tools such as from Symtavision (https://www.symtavision.com/), Timing Architects (http://www.timing-architects.com/), and Inchron (https://www.inchron.de/). Thereby, the focus will lie on determining tight end-to-end latency bounds for a set of given cause-effect chains. This is challenging since the dynamic behavior of a engine management software is quite complex and contains mechanisms that explore the limits of existing academic approaches: preemptive and cooperative priority based scheduling; periodic, sporadic, and engine synchronous tasks; multi-core platform with distributed cause-effect chains including cross-core communication; label (i.e. data) placement dependent execution times of runnables Overall the demo gives an impression of the current state-of-practice in industrial product development, and serves as baseline for further academic research.","PeriodicalId":338179,"journal":{"name":"2016 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTAS.2016.7461330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
The complex dynamic behavior of automotive software systems, in particular engine management, in combination with emerging multi-core execution platforms, significantly increased the problem space for timing analysis methods. As a result, the risk of divergence between academic research and industrial practice is currently increasing. Therefore, we provided a concrete automotive benchmark for the Formal Methods for Timing Verification (FMTV) challenge 2016 (https://waters2016.inria.fr/challenge/), a full blown performance model of a modern engine management system (downloadable at http://ecrts.eit.uni-kl.de/forum/viewtopic.php?f=27&t=62), with the goal to challenge existing timing analysis approaches with respect to their expressiveness and precision. In the demo session we will present the performance model of the engine management system using the Amalthea tool (http://www.amalthea-project.org/). Furthermore, we will show the model in action using professional timing tools such as from Symtavision (https://www.symtavision.com/), Timing Architects (http://www.timing-architects.com/), and Inchron (https://www.inchron.de/). Thereby, the focus will lie on determining tight end-to-end latency bounds for a set of given cause-effect chains. This is challenging since the dynamic behavior of a engine management software is quite complex and contains mechanisms that explore the limits of existing academic approaches: preemptive and cooperative priority based scheduling; periodic, sporadic, and engine synchronous tasks; multi-core platform with distributed cause-effect chains including cross-core communication; label (i.e. data) placement dependent execution times of runnables Overall the demo gives an impression of the current state-of-practice in industrial product development, and serves as baseline for further academic research.