# Automating the Analysis of Negative Test Verdicts:
## 1 Introduction  
A malfunctioning automotive embedded system can potentially cause serious accidents, endangering the safety of people. Therefore, it is important to detect any defects in the embedded software through various testing processes [1]. Guaranteeing the correct operation of the electronic systems incorporating the vehicle is highly complex, and their expected functionality must be ensured in extremely adverse environmental conditions. In fact, vehicles are exposed to vibration, noise, extreme temperatures and electromagnetic fields that can affect and degrade electronic components [2]. To test embedded software as quickly and comprehensively as possible, verification and validation of its functionality and quality should start as early as possible. Embedded system vendors aim to automate testing processes in order to reduce the cost and time required for testing. This is especially crucial in the context of the complexity and variety of features being tested. [PERSON] points out that effective automation requires control over all data entered into the system that can affect the output values, including data from external systems we depend on [3]. Test automation is becoming a key element in the testing process, which consists of three stages: test case generation, test execution, and result analysis [1]. Artificial intelligence is anticipated to impact testing across a wide range of software domains, including but not limited to mobile and web applications, IoT, embedded systems, database applications, the gaming industry, real-time applications, and critical applications [4]. [PERSON] [5] mentions in his article that AI already enhances the software testing process in various aspects. The first step in the testing process in which artificial intelligence algorithms can be involved is the analysis of functional requirements and the automatic generation of test cases. [PERSON] and [PERSON] [6] suggest an approach based on the natural language processing technique, requiring an automation tool and the usage of a database to store the generated graphs. [PERSON] [7] also propose a system based on NLP which can reduce the effort and time consumed by the software tester by extracting test cases automatically from Software Requirement Specification. [PERSON] et al. use model-free reinforcement learning to construct a self-adaptive autonomous stress-testing structure. This structure is able to obtain the optimal policy for generating stress test cases without having a model of the system under test. The experimental analysis results show that the proposed intelligent structure effectively and adaptively generates stress test conditions for different software systems, even in the absence of performance models [8]. [PERSON] et al. introduce a technique for the automatic extraction of homogeneous test cases from requirement specification documents, eliminating dependency on the skills and expertise of the engineer tasked with test case creation [9]. Based on the results of the [PERSON] et al. study, it can be concluded that the application of artificial intelligence techniques has significantly improved the test case generation and design process. The authors mention that recent research has mainly focused on areas such as test case generation, prioritization, data generation, and oracle construction. It is worth noting that some software testing activities, including test harness implementation, test technique selection, test repair and vulnerability analysis, are omitted from their manuscript due to the limited availability of AI-based research in these areas [4]. Complex system functionality, changing customer requirements, and evolving regulations, especially in the automotive industry, lead to changes in embedded systems during and after development. This requires repeating the testing process with each software or hardware change, emphasizing the need for test automation to reduce costs, shorten the overall process, and improve efficiency [10].