der Universität des Saarlandes

For hard real-time applications, tight provable bounds on the application’s worst-case execution time must be derivable. Employing dynamic memory allocation, in general, significantly decreases an application’s timing predictability. In conse-quence, current hard real-time applications rely on static memory management. This thesis studies how the predictability issues of dynamic memory allocation can be overcome and dynamic memory allocation be enabled for hard real-time applications. We give a detailed analysis of the predictability challenges imposed on current state-of-the-art timing analyses by dynamic memory allocation. We propose two approaches to overcome these issues and enable dynamic memory allocation for hard real-time systems: automatically transforming dynamic into static allocation and using a novel, cache-aware and predictable memory allo-cator. Statically transforming dynamic into static memory allocation allows for very precise WCET bounds as all accessed memory addresses are completely known. However, this approach requires much information about the applica-tion’s allocation behavior to be available statically. For programs where a static precomputation of a suitable allocation scheme is not applicable, we investigate approaches to construct predictable dynamic memory allocators to replace the stan-dard, general-purpose allocators in real-time applications. We present evaluations of the proposed approaches to evidence their practical applicability.