An implementation-oriented algorithm for lazy code motion is presented that minimizes the number of computations in programs while suppressing any unnecessary code motion in order to avoid superfluous register pressure. In particular, this variant of the original algorithm for lazy code motion works on flowgraphs whose nodes are basic blocks rather than single statements, since this format is standard in optimizing compilers. The theoretical foundations of the modified algorithm are given in the first part, where t -refined flowgraphs are introduced for simplifying the treatment of flow graphs whose nodes are basic blocks. The second part presents the “basic block” algorithm in standard notation and gives directions for its implementation in standard compiler environments.

Real-time systems need time-predictable platforms to allow static analysis of the worst-case execution time (WCET). Standard multi-core processors are optimized for the average case and are hardly analyzable. Within the T-CREST project we propose novel solutions for time-predictable multi-core architectures that are optimized for the WCET instead of the average-case execution time. The resulting time-predictable resources (processors, interconnect, memory arbiter, and memory controller) and tools (compiler, WCET analysis) are designed to ease WCET analysis and to optimize WCET performance. Compared to other processors the WCET performance is outstanding.The T-CREST platform is evaluated with two industrial use cases. An application from the avionic domain demonstrates that tasks executing on different cores do not interfere with respect to their WCET. A signal processing application from the railway domain shows that the WCET can be reduced for computation-intensive tasks when distributing the tasks on several cores and using the network-on-chip for communication. With three cores the WCET is improved by a factor of 1.8 and with 15 cores by a factor of 5.7.The T-CREST project is the result of a collaborative research and development project executed by eight partners from academia and industry. The European Commission funded T-CREST.

We present an interprocedural generalization of the well-known (intraprocedural) Coincidence Theorem of Kam mad Ullman, which provides a sufficient condition for the equivalence of the meet over all paths (MOP) solution and the maximal fi~ed point (MFP) solution to a data flow analysis problem. This generalization covers arbitrary imperative programs with recursive procedures, global and local variables, and formal value parameters. In the absence of procedures, it reduces to the classical intraprocedural version. In particular, Our stack-based approach generalizes the coincidence theorems of Barth and Sharir/Pnueli for the same setup, which do not properly deal with local variables of reeursive procedures.

In this paper we s h o w h o w to construct optimal bitvector analysis algorithms for parallel programs with shared memory that are as e cient as their purely sequential counterparts, and which can easily be implemented. Whereas the complexity result is rather obvious, our optimality result is a consequence of a new Kam/Ullman-style Coincidence Theorem. Thus, the important merits of sequential bitvector analyses survive the introduction of parallel statements.

We show that recent progress in extending the automatatheoretic approach to model-checking beyond the class of nite-state processes nds a natural application in the area of interprocedural dataow analysis.