Tight integration of cache, path and task-interference modeling for the analysis of hard real time systems

Traditional timing analysis for hard real-time systems is a two-step approach consisting of isolated per-task timing analysis and subsequent scheduling analysis which is conceptually entirely separated and is based only on execution time bounds of whole tasks. Today this model is outdated as it relies on technical assumptions that are not feasible on modern processor architectures any longer. The key limiting factor in this traditional model is the interfacing from micro-architectural analysis of individual tasks to scheduling analysis — in particular path analysis as the binding step between the two is a major obstacle. In this thesis, we contribute to traditional techniques that overcome this problem by means of by passing path analysis entirely, and propose a general path analysis and several derivatives to support improved interfacing. Specifically, we discuss, on the basis of a precise cache analysis, how existing metrics to bound cache-related preemption delay (CRPD) can be derived from cache representation without separate analyses, and suggest optimizations to further reduce analysis complexity and to increase accuracy. In addition, we propose two new estimation methods for CRPD based on the explicit elimination of infeasible task interference scenarios. The first one is conventional in that path analysis is ignored, the second one specifically relies on it. We formally define a general path analysis framework in accordance to the principles of program analysis — as opposed to most existing approaches that differ conceptually and therefore either increase complexity or entail inherent loss of information — and propose solutions for several problems specific to timing analysis in this context. First, we suggest new and efficient methods for loop identification. Based on this, we show how path analysis itself is applied to the traditional problem of per-task worst-case execution time bounds, define its generalization to sub-tasks, discuss several optimizations and present an efficient reference algorithm. We further propose analyses to solve related problems in this domain, such as the estimation of bounds on best-case execution times, latest execution times, maximum blocking times and execution frequencies. Finally, we then demonstrate the utility of this additional information in scheduling analysis by proposing a new CRPD bound