Intelligent automotive electronics significantly improved driving safety in the last decades. With the increasing complexity of automotive systems, dependability of the electronic components themselves and of their interaction must be assured to avoid any risk to driving safety due to unexpected failures caused by internal or external faults.

In this article, we present a virtual platform driven methodology for model-based design of dependable SW targeting cyber-physical systems. Our methodology covers an eight levels spanning flow for smooth refinement of discrete/continuous application models towards the implementation of distributed SW stacks providing flexibility w.r.t. early integration of object/binary code. For this, we propose multiple virtual platform abstraction levels supporting SW synthesis from high level MoCs. By continuous interfacing with a model of the physical environment in-the-loop we enable to holistically consider mutual impacts of the SW and its environment. In order to assess and improve SW dependability we investigate the injection of faults and their effects into both the environment model and the SW under test. We present a mapping of the proposed methodology to a completely SystemC-based framework by employing several SystemC extensions, such as AMS/TDF, QEMU, and abstract models of RTOS, HAL and middleware. Finally, we present experimental results from an automotive case study: a fault- tolerant fuel injection control system for which we consider two fault injection use cases: (i) robustness/stress testing and (ii) mutation testing. Our results were derived by prototypic integration of our SystemC framework with a commercial Simulink- based tool chain for AUTOSAR-compliant SW development and deployment.

This paper presents a novel mutation based testing method through binary mutation. For this, a table of mutants is derived by control flow analysis of a disassembled binary under test. Mutations are injected at runtime by dynamic translation. Thus, our approach neither relies on source code nor a certain compiler. As instrumentation is avoided, testing results correspond to the original binary. In addition to high-level language faults, the proposed approach captures target specific faults related to compiling and linking. We investigated the software of an automotive case study. For this, a taxonomy of mutation operators for the ARM instruction set is proposed. Our experimental results prove 100% accuracy w.r.t. confidence metrics provided by conventional testing methods while avoiding significant mutant compilation overhead. Further speed up is achieved by an efficient binary mutation testing framework that relies on extending the open source software emulator QEMU.

This paper presents the XEMU framework for mutation based testing of embedded software binaries. We apply an extension of the QEMU software emulator, which injects mutations at run-time by dynamic code translation without affecting the binary software under test. The injection is based on a mutation table, which is generated by control flow graph (CFG) analysis of the disassembled code prior to its execution without presuming access to source code. We introduce our approach by the example of the ARM instruction set architecture for which a mutation taxonomy is presented. In addition to extending the testing scope to target specific low level faults, XEMU addresses the reduction of the mutants creation, execution, and detection overheads. Moreover, we reduce testing efforts by applying binary CFG analysis and constraint-based test generation for improved test quality. The experimental results of a car motor management software show significant improvements over conventional source code based approaches while providing 100% accuracy in terms of the computed test quality metrics.

Mutation analysis is a powerful tool for white-box testing of the verification environment in order to produce dependable and higher quality software products. However, due to high computational costs and the focus on high-level software languages such as Java mutation analysis is not yet widely used in commercial design flows targeting embedded (software) systems. Here the industry is modeling both hardware and related software parts at higher levels of abstraction, called virtual prototypes, to accelerate parallel development and shorten time-to-market. In this paper we propose a mutation testing verification flow for SystemC based virtual prototypes that may not rely on source code only but on annotated basic blocks and enables mutant creation at assembler level to heavily reduce execution costs and equivalence mutants likelihood.

Safety-critical automotive systems must fulfill hard real-time constraints for reliability and safety. This paper presents a case study for the application of an AUTOSAR-based language for timing modeling and analysis. We present and apply the Timing Augmented Description Language (TADL) and demonstrate a methodology for the development of a speed-adaptive steer-by-wire system. We examine the impact of TADL and the methodology on the development process and the suitability and interoperability of the applied tools with respect to the AUTOSAR-based tool chain in the context of our case study.