Quality Attribute

Quality attributes in software and data science encompass various characteristics impacting system performance, reliability, and maintainability, with current research focusing on improving their assessment and prediction. This involves developing novel methods for evaluating quality in diverse contexts, such as machine learning model testing, music generation, and video quality assessment, often leveraging advanced techniques like deep learning (e.g., transformers, diffusion models) and Koopman operators. Improved quality attribute analysis is crucial for enhancing the reliability and trustworthiness of complex systems, particularly in machine learning applications, and for optimizing software development processes. The ultimate goal is to create more robust and efficient systems across various domains.