Abstract

For many years, automotive embedded systems have been validated only by testing. In the near future, Advanced Driver Assistance Systems (ADAS) will take a greater part in the car’s software design and development. Furthermore, their increasing critical level may lead authorities to require a certification for those systems. We think that bringing formal proof in their development can help establishing safety properties and get an efficient certification process. Other industries (e.g. aerospace, railway, nuclear) that produce critical systems requiring certification also took the path of formal verification techniques. One of these techniques is deductive proof. It can give a higher level of confidence in proving critical safety properties and even avoid unit testing.In this paper, we chose a production use case: a function calculating a square root by linear interpolation. We use deductive proof to prove its correctness and show the limitations we encountered with the off-the-shelf tools. We propose approaches to overcome some limitations of these tools and succeed with the proof. These approaches can be applied to similar problems, which are frequent in the automotive embedded software.

Highlights

  • Introduction and MotivationToday, the automotive industry relies mostly on a model-based approach for developing embedded software

  • We proved our goals with Colibri, CVC4 and Yices2

  • We have presented our experiments with automatic deductive proof of correctness of a discrete-valued function calculating a square root by interpolation

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Summary

Introduction

The automotive industry relies mostly on a model-based approach for developing embedded software. It consists in connecting common library blocks (operators) to design and simulate a model of the behavior to be produced. It uses a higher level of abstraction than the code. Code with the behavior of the model is produced automatically. The main advantage of this approach is that models can be simulated and debugged before code generation. The implementation of a model on a specific hardware can bring behaviors that have not been seen before at design stage

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