Statistical Analysis Of Energy-Aware Real-Time Automotive Systems In East-Adl/Stateflow

EAST-ADL is an architectural description language dedicated to safety-critical automotive embedded system design. We have previously modified EAST-ADL to include energy constraints and transformed energy-aware real-time behavioral constraints in EAST-ADL into analyzable UPPAAL models. In this paper, we extend our previous work by including support for Stateflow, which is used to design event-driven systems via hierarchical state machines and flow charts. However, Stateflow provides limited support for formal analysis and often suffers from incomplete coverage issues since it was originally designed for the simulation of designs and as such does not provide a model amenable to formal verification. We tackle that shortcoming by transforming Stateflow models into verifiable UPPAAL models with stochastic semantics and integrating the translation with formal statistical analysis techniques: a flattening strategy and a set of mapping rules are proposed to facilitate the guarantee of translation. The analysis techniques, including the flattening and mapping strategy, are validated and demonstrated on the Fault-Tolerant Fuel Control case study.