Integrated Modular Avionics enables applications of different criticality levels to share the same hardware platform with an established temporal and spatial isolation. On-chip communication systems for such platforms must support different bandwidth and latency requirements of applications while preserving time predictability. In this paper, our concern is a time-predictable on-chip network architecture for targeting applications in mixed-criticality aerospace systems. The proposed architecture introduces a mixed, priority-based and time-division-multiplexed arbitration scheme to accommodate different bandwidth and latency in the same network while preserving worst-case time predictability for end-to-end communication without packet loss. Furthermore, as isolation of erroneous transmission by a faulty application is a key aspect of contingency management, the communication system should support isolation mechanisms to prevent interference. For this reason, a sampling port and isolated sampling buffer-based approach is proposed with a transmission authorisation control mechanism, guaranteeing spatial and temporal isolation between communicating systems.

This paper introduces a new logic-based method for optimising the selection of compiler flags on embedded architectures. In particular, we use Inductive Logic Programming (ILP) to learn logical rules that relate effective compiler flags to specific program features. Unlike earlier work, we aim to infer human-readable rules and we seek to develop a relational first-order approach which automatically discovers relevant features rather than relying on a vector of predetermined attributes. To this end we generated a data set by measuring execution times of 60 benchmarks on an embedded system development board and we developed an ILP prototype which outperforms the current state-of-the-art learning approach in 34 of the 60 benchmarks. Finally, we combined the strengths of the current state of the art and our ILP method in a hybrid approach which reduced execution times by an average of 8% and up to 50% in some cases.