Pragmatic Approaches for Timing Analysis of Real-Time Embedded Systems

Abstract: Many industrial real-time embedded systems are very large, flexible and highly configurable software systems. Such systems are becoming ever more complex, and we are reaching the stage where even if existing timing analysis was feasible from a cost and technical perspective, the analysis results are overly pessimistic, making them less useful to the practitioner. When combined with the fact that most existing real-time embedded systems tend to be probabilistic in nature due to high complexity featured by advanced hardware and more flexible and/or adaptive software applications, this advocates moving toward pragmatic timing analysis, which are not specifically limited by constrains related to intricate task execution and temporal dependencies in systems. In this thesis, we address this challenge, and we present two pragmatic timing analysis techniques for real-time embedded systems.The first contribution is a simulation-based analysis using two simple yet novel search algorithms of meta-heuristic type, i.e., a form of genetic algorithms and hill-climbing with random restarts, yielding substantially better results, comparing traditional Monte Carlo simulation-based analysis techniques.As the second contribution, we discuss one major issue when using simulation-based methods for timing analysis of real-time embedded systems, i.e., model validity, which determines whether a simulation model is an accurate representation of the system at the certain level of satisfaction, from a task response time and execution time perspective.The third contribution is a statistical timing analysis which, unlike the traditional timing analysis, does not require worst-case execution times of tasks as inputs, and computes a probabilistic task worst-case response time estimate pertaining to a configurable task reliability requirement.In addition, a number of tools have been implemented and used for the evaluation of our research results. Our evaluations, using dierent simulation models depicting fictive but representative industrial control applications, have shown a clear indication that our new timing analysis techniques have the potential to be both applicable and useful in practice, as well as being complementary to software testing focusing on timing properties of real-time embedded systems that are used in the domains of industrial automation, aerospace and defense, automotive telematics, etc.