Test case development for complex automotive systems is a tedious job because of the vast number of requirements, dependencies, and strict compliance standards that must be satisfied. Manually creating these test cases is time-consuming, error-prone, and often leads to gaps in coverage. In this article, we will see how we can leverage LLM to automate the process.

In the era of AI voice assistants, most systems rely heavily on the cloud for speech recognition, raising concerns about data privacy, security, and the need for constant internet connectivity. To address these challenges, AI-driven offline voice assistants are used. Such offline voice assistants are especially crucial in automotive systems, where reliable voice control over in-car functions must remain available even in areas with poor cellular coverage.

In this article, we will discuss a challenge we faced while implementing natural language commands and the solution we adopted to overcome it.