A grand challenge in complex embedded systems design is developing methods and tools for modeling and analyzing the behavior of an application software running on multicore or distributed platforms. We propose a rigorous method and a tool chain that allows to obtain a faithful model representing the behavior of a mixed hardware/software system from a model of its application software and a model of its underlying hardware architecture. The system model can be simulated and analyzed for validation of both functional and extra-functional properties. The tool chain uses DOL (Distributed Operation Layer [1]) as the frontend for specifying the application software and hardware architecture, and BIP (Behavior Interaction Priority [2]) as the modeling and analysis framework. It is illustrated through the construction of system models of MJPEG and MPEG2 decoder applications running on MPARM, a multicore architecture.

Autonomous robots are complex systems that require the interaction/cooperation of numerous heterogeneous software components. Nowadays, robots are critical systems and must meet safety properties including in particular temporal and real-time constraints. We present a methodology for modeling and analyzing a robotic system using the BIP component framework integrated with an existing framework and architecture, the LAAS Architecture for Autonomous System, based on Geno

We apply a model construction methodology to TinyOS- based networks, using the behavior-interaction-priority (BIP) component framework. The methodology consists in building the model of a node as the composition of a model extracted from a nesC program describing the application, and models of TinyOS components. Models for networks are obtained by composition of models for nodes by using BIP connectors implementing different types of radio chan- nels. This opens the way for enhanced analysis and early error detection by using verification techniques.

We present a methodology for modeling heterogeneous real-time components. Components are obtained as the superposition of three layers: behavior, specified as a set of transitions; Interactions between transitions of the behavior; Priorities, used to choose amongst possible interactions. A parameterized binary composition operator is used to compose components layer by layer. We present the BIP language for the description and composition of layered components as well as associated tools for executing and analyzing components on a dedicated platform. The language provides a powerful mechanism for structuring interactions involving rendezvous and broadcast. We show that synchronous and timed systems are particular classes of components. Finally, we provide examples and compare the BIP framework to existing ones for heterogeneous component-based modeling