Integration of Artificial Intelligence into Software Component Reuse: An Overview of Software Intelligence

Abstract

Artificial Intelligence (AI) is transforming software component reuse by enhancing automation, efficiency, and intelligent retrieval of reusable software artifacts. Traditional reuse methods face challenges in retrieving, classifying, and recommending components due to the complexity of software repositories. AI-driven techniques such as machine learning (ML), natural language processing (NLP), and knowledge graphs help overcome these limitations by enabling intelligent categorization and recommendation. Software Intelligence (SI) enhances reuse by employing data mining techniques to extract patterns from large repositories. A centralized AI-powered repository improves component discovery, allowing developers to find and integrate relevant components efficiently. NLP enhances semantic understanding, enabling better classification and retrieval of software components. However, AI-driven software reuse presents challenges, including data quality, interoperability, and AI model integration. Future research should focus on improving automation through deep learning, refining repository structures, and optimizing recommendation systems. Ethical concerns, such as bias in AI recommendations and intellectual property rights, must also be addressed.