SageMinder: AI-Driven Technical Debt Reduction in AWS-Based Data Science Pipelines
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
How to Cite?: Sai Tarun Kaniganti, "SageMinder: AI-Driven Technical Debt Reduction in AWS-Based Data Science Pipelines", Volume 12 Issue 6, June 2023, International Journal of Science and Research (IJSR), Pages: 2988-2996, https://www.ijsr.net/getabstract.php?paperid=SR24806050008, DOI: https://dx.doi.org/10.21275/SR24806050008