Title: COBRA-HPA: a block generating tool to perform hybrid program analysis

Authors: Thomas Huybrechts; Yorick De Bock; Haoxuan Li; Peter Hellinckx

Addresses: University of Antwerp - imec, IDLab, Faculty of Applied Engineering, Antwerp, Belgium ' University of Antwerp - imec, IDLab, Faculty of Applied Engineering, Antwerp, Belgium ' University of Antwerp - imec, IDLab, Faculty of Applied Engineering, Antwerp, Belgium ' University of Antwerp - imec, IDLab, Faculty of Applied Engineering, Antwerp, Belgium

Abstract: The Worst-Case Execution Time (WCET) of a task is an important value in real-time systems. This metric is used by the scheduler in order to schedule all tasks before their deadlines. However, the code and hardware architecture have a significant impact on the execution time and thus the WCET. Therefore, different analysis methodologies exist to determine the WCET, each with their own advantages and/or disadvantages. In this paper, a hybrid approach is proposed which combines the strengths of two common analysis techniques. The two-layer hybrid model splits the code of tasks into so-called basic blocks. The WCET can be determined by performing execution time measurements on each block and statically combining those results. The COBRA-HPA framework presented in this paper is developed to facilitate the creation of hybrid block models and automate the measurements/analysis process. Additionally, an elaborated discussion on the implementation and performance of the framework is given. In conclusion, the results of the COBRA-HPA framework show a significant reduction in analysis effort while keeping sound WCET predictions for the hybrid method compared to the static and measurement-based approach.

Keywords: WCET; worst-case execution time; hybrid analysis methodology; code behaviour framework; COBRA; basic block generator.

DOI: 10.1504/IJGUC.2019.098211

International Journal of Grid and Utility Computing, 2019 Vol.10 No.2, pp.105 - 118

Received: 26 Jan 2017
Accepted: 08 Sep 2017
Published online: 06 Mar 2019 *

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