Worst-Case Execution Time Analysis for C++ based Real-Time On-Board Software Systems

Abstract

Autonomous systems are today’s trend in the aerospace domain. These systems require more on-board data processing capabilities. They follow data-flow programming, and have similar software architecture. Developing a framework that is applicable for these architectures reduces the development efforts and improves the re-usability. However, its design’s essential requirement is to use a programming language that can offer both abstraction and static memory capabilities. As a result, C++ was chosen to develop the Tasking Framework, which is used to develop on-board data-flow-oriented applications. Validating the timing requirements for such a framework is a long, complicated process. Estimating the worst-case execution time (WCET) is the first step within this process. Thus, in this thesis, we focus on performing WCET analysis for C++ model-based applications developed by the Tasking Framework. This work deals with two main challenges that emerged from using C++: using objects impose the need for a memory model and using virtual methods implicate indirect jumps. To this end, we developed a tool based on symbolic execution that can handle both challenges. The tool showed high precision of early 90 % in bounding loops of the Benchmark suit. We then integrated our advanced analysis with an open toolbox for adaptive WCET analysis. Finally, we evaluated our approach for estimating the WCET for tasks developed by the Tasking Framework.