Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
In this paper, we study the maintenance of role-based access control (RBAC) models in database environments using transitive closure relations. In particular, the algorithms that ...
Software components are modular and can enable post-deployment update, but their high overhead in runtime and memory is prohibitive for many embedded systems. This paper proposes ...
We explain the design of the interpretation-based static analyzer Astr´ee and its use to prove the absence of run-time errors in safety-critical codes. Categories and Subject Des...
Design space exploration of embedded systems typically focuses on classical design goals such as cost, timing, buffer sizes, and power consumption. Robustness criteria, i.e. sensi...