Core Viewpoint - The automotive industry is facing increasing challenges in ensuring the reliability and quality of integrated circuits and systems, particularly as vehicles become more reliant on advanced driver-assistance systems (ADAS) and software-defined functionalities [2][4][19]. Group 1: Challenges in Automotive Chip Development - The traditional development cycle for automotive chips is five to seven years, but the shift towards ADAS and complex infotainment systems has accelerated this process [2][4]. - Achieving automotive-grade quality with a defect rate below one part per million (DPPM) is a significant challenge, necessitating innovative testing methods [2][4]. - Manufacturers are under pressure to maintain low testing costs while ensuring high quality, creating a delicate balance [2][4][5]. Group 2: Advances in ADAS and Software-Defined Vehicles - ADAS has driven the automotive industry towards smaller technology nodes and more complex systems, transitioning to fully software-defined vehicles (SDVs) [4][5]. - The shift to advanced nodes below 5nm presents reliability and safety challenges, particularly for systems expected to operate for extended periods [4][5][19]. - Most new vehicles are currently at Level 2 or Level 3 automation, with increasing safety standards required for higher levels of automation [7][8]. Group 3: Testing and Quality Assurance - Automotive chips must undergo rigorous testing at three temperature extremes to simulate operational conditions, as defined by AEC-Q100 standards [9]. - Machine learning-based anomaly detection methods are increasingly used to enhance quality levels close to zero DPPM [9][10]. - Advanced fault models are being developed to better simulate common defects in silicon, improving testing accuracy [10]. Group 4: Virtual Testing and Predictive Maintenance - Virtual testing is becoming essential to reduce the complexity of real-world testing, allowing for parallel development and faster time-to-market [8][19]. - Continuous monitoring and feedback throughout the vehicle's lifecycle are critical, especially as more advanced nodes are introduced [19]. - On-chip monitoring and machine learning are being utilized to track performance degradation and predict failures [18][19]. Group 5: Future Directions in Automotive Testing - The industry is moving towards chiplet-based designs to improve yield and reuse rates while managing the complexity of advanced packaging [12][13]. - Acoustic and optical technologies are being employed to analyze inter-chip bonding characteristics, which are crucial for reliability [14]. - System-level testing is becoming a standard requirement to ensure that both hardware and software meet functional and non-functional requirements [16].