Performance Issue

Performance issues, encompassing unexpected slowdowns or failures in diverse systems, are a significant challenge across numerous fields. Current research focuses on identifying root causes, often employing machine learning models like transformers and graph attention networks to analyze complex datasets of system metrics and code behavior. This work aims to improve anomaly detection, root cause analysis, and automated performance bug fixing, ultimately leading to more reliable and efficient systems in areas ranging from cloud computing and high-performance networks to music education and medical image processing. The development of standardized datasets and evaluation benchmarks is crucial for advancing this research and facilitating the comparison of different approaches.