Nowadays, applications from dissimilar domains, such as high-performance computing and high-integrity systems, require levels of performance that can only be achieved by means of sophisticated heterogeneous architectures. However, the complex nature of such architectures hinders the production of efficient code at acceptable levels of time and cost. Moreover, the need for exploiting parallelism adds complications of its own (e.g., deadlocks, race conditions,...). In this context, compiler analysis is fundamental for optimizing parallel programs. There is however a trade-off between complexity and profit: low complexity analyses (e.g., reaching definitions) provide information that may be insufficient for many relevant transformations, and c...