Software Classification

Software classification aims to automatically categorize software artifacts, such as code comments, logs, or entire projects, based on their characteristics. Current research focuses on leveraging deep learning architectures, including convolutional neural networks (CNNs) for structured data like logs and graph attention networks for code's hierarchical structure, as well as incorporating large language models (LLMs) and generative AI for data augmentation and improved classification accuracy. These advancements are improving software development processes, enabling automated defect detection, enhanced code understanding, and more efficient software project management. The development of robust and accurate software classification methods has significant implications for software quality, maintainability, and the overall efficiency of software engineering.