Software Failure

Software failure research aims to understand and mitigate the causes and consequences of software malfunctions across diverse domains. Current research focuses on leveraging machine learning, particularly large language models (LLMs) and other deep learning architectures, to analyze failure patterns, predict risks, and improve software robustness. This work is crucial for enhancing software reliability and safety in critical applications, from autonomous vehicles to healthcare systems, and for improving the efficiency of software development processes. Furthermore, research is exploring methods to improve the explainability of AI models used in software analysis and to develop more robust and reliable models themselves.