SageMinder: AI-Driven Technical Debt Reduction in AWS-Based Data Science Pipelines

Sai Tarun Kaniganti

Abstract: This paper focuses on the difficulty of managing technical debt in large-scale software projects that use AI and Machine Learning for identification and resolution. The approach consists of systematic surveillance of technical debts, gradualistic refinancing techniques, emphasis on sustaining high-quality standards, and automatic tools for detecting technical debt. When implemented in the development lifecycle, such strategies will improve the software projects' stability and sustainability in the long run.

Keywords: Technical Debt, Artificial Intelligence, Machine Learning, Amazon Web Service, Software Engineering, Debt, Code Quality, DevOps, Data Science, Cloud Computing