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Software developers in the automotive sector must achieve high quality objectives. Many design and implementation errors are avoided by synthesizing code from model-based software specifications using automatic code generators such as ETAS' ASCET. To verify non-functional properties of the implementation, model-based design processes should be complemented with static program analysis tools like AbsInt's StackAnalyzer and timing analyzer aiT. ASCET, StackAnalyzer and aiT can be integrated in a way that the analysis results for code generated by ASCET are conveniently accessible from within the ASCET development environment. This gives ASCET users a direct feedback on the effects of their design decisions on resource usage, allowing to select more efficient designs and implementation methods. In the paper, we present the tools, the experimental integration, preliminary results and plans for further tool integration.

In modern vehicles the architecture of electronics is growing more and more complex because both the number of electronic functions – e.g. implemented as software modules – as well as the level of networking between electronic control units (ECUs) is steadily increasing. This complexity leads to greater propagation of failure symptoms, and diagnosing the causes of failure becomes a new challenge. Diagnostics aims at detecting failures such as defect sensors or faulty communication messages. It is subdivided into diagnosis algorithms on an ECU and algorithms running offboard, e.g. on a diagnostic tester. These algorithms have to complement each other in the best possible way. While in the past the diagnosis algorithm was developed late in the development process, nowadays there are efforts to start the development of such algorithms earlier – at least in parallel to developing a new feature itself. This would allow developers to verify the diagnosis algorithms in early design stages.

Model-based development and autocoding have become common practice in the automotive industry over the past few years. The industry is using these methods to tackle a situation in which complexity is constantly growing and development times are constantly decreasing, while the safety requirements for the software stay the same or even increase. The debate is no longer whether these methods are useful, but rather on the conditions for achieving optimum results with them. From the experiences made during the last decade this paper shows some of the key factors helping to achieve success when introducing or extending the deployment of automatic code generation in a model-based design process.

Over the last few years the introduction of explicit system and software architecture models (e.g. AUTOSAR models) has led to changes in the automotive development process. The ability to simulate these models on a PC will be decisive for the acceptance of such approaches. This would support the early verification of distributed ECU and software systems and could therefore lead to cost savings. This paper describes an implementation of such an approach which fits into current development processes.

Developers of safety-critical real-time systems have to ensure that their systems react within given time bounds. Ideally, the system is designed to provide sufficient computing power and network bandwidth, is cost efficient and provides the necessary safety level. To achieve this goal, three challenges have to be addressed. First, it must be possible to account for timing during early development stages in the architecture exploration phase. Second, during software development, timing behavior and the effects of software changes on timing must be observable. Third, there must be a technology for formally verifying the final timing behavior for industry-size applications. In this article we present a comprehensive methodology for dealing with timing which addresses all three issues based on state-of-the-art commercial tools.

Model-based development is the established way of developing embedded control algorithms, especially for safety-critical applications. The aim is to improve development efficiency and safety by developing the software at a high abstraction level (the model) and by generating the implementation (the C code) automatically from the model. Although model-based development focuses on the models themselves, downstream artifacts such as source code or executable object code have to be considered in the verification stage. Safety standards such as ISO 26262 require upper bounds to be determined for the required storage space or the execution time of real-time tasks, and the absence of run-time errors to be demonstrated. Static analysis tools are available which work at the code level and can prove the absence of such errors. However, the connection to the model level has to be explicitly established.

Model-based software development and automatic code generation have become increasingly established in recent years. The automotive industry has widely adopted and successfully deployed these methods in many different series production programs worldwide. This brought various benefits, such as a reduction in development times, improved quality due to more precise specifications, and early verification and validation by means of simulation. At the same time, more and more safety-related and safety-critical systems have been - and will be -introduced into modern vehicles. Common examples are active front steering, adaptive cruise-control, and integrated chassis control. This leads to the question, if and how model-based design and automatic production code generation can be applied to the development of safety-critical systems.