In this paper, we present a novel industry dataset on static software and change metrics for Matlab/Simulink models and their corresponding auto-generated C source code. The data set comprises data of three automotive projects developed and tested accordingly to industry standards and restrictive software development guidelines. We present some background information of the projects, the development process and the issue tracking as well as the creation steps of the dataset and the used tools during development. A specific highlight of the dataset is a low measurement error on change metrics because of the used issue tracking and commit policies.
Increasingly intelligent energy-management and safety systems are developed to realize safe and economic automobiles. The realization of these systems is only possible with complex and distributed software. This development poses a challenge for verification and validation. Upcoming standards like ISO 26262 provide requirements for verification and validation during development phases. Advanced test methods are requested for safety critical functions. Formal specification of requirements and appropriate testing strategies in different stages of the development cycle are part of it. In this paper we present our approach to formalize the requirements specification by test models. These models serve as basis for the following testing activities, including the automated derivation of executable test cases from it. Test cases can be derived statistically, randomly on the basis of operational profiles, and deterministically in order to perform different testing strategies. We have applied our approach with a large German OEM in different development stages of active safety and energy management functionalities. The test cases were executed in model-in-the-loop and in hardware-in-the-loop simulation. Errors were identified with our approach both in the requirement specification and in the implementation that were not discovered before.
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