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|Title:||PRECISE YET SCALABLE RESOURCE ANALYSIS VIA SYMBOLIC EXECUTION||Authors:||RASOOL MAGHAREH||Keywords:||Symbolic Execution, Worst-case Resource Analysis, WCET, Memory High-watermark, WCEC, Real-time Systems||Issue Date:||28-Jul-2016||Citation:||RASOOL MAGHAREH (2016-07-28). PRECISE YET SCALABLE RESOURCE ANALYSIS VIA SYMBOLIC EXECUTION. ScholarBank@NUS Repository.||Abstract:||The expanding complexity of embedded systems has emerged the need for techniques to perform resource analysis. This thesis makes several contributions in the area of worst-case resource consumption analysis. First, an integrated analysis framework is presented where micro-architectural modeling and systematic path-sensitivity are synergized. Integrated resource analysis would give us a high precision for resource analysis, but at the same time, it is a huge challenge for scalability. Our contribution is then a dynamic programming algorithm with a powerful concept of reuse. Reuse, in turn, depends on the core concepts of interpolation and dominance. Our setting is novel not just because we are performing interpolation for resource analysis, but because our interpolation with dominance covers reuse under an environment where resource consumption of program paths is dynamic and/or symbolic. Next, the analysis framework is customized for Worst-case Execution Time Analysis, Symbolic Memory High-watermark Analysis and finally Worst-case Energy Consumption Analysis.||URI:||http://scholarbank.nus.edu.sg/handle/10635/134930|
|Appears in Collections:||Ph.D Theses (Open)|
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