The aim of this research team

This research team aims to study technical debt in AI-enabled systems and develop a framework for AI-based software development companies for early detection, tracking and prevention of issues that arise from a TD perspective. The need for this framework stems from process and quality management issues that are caused by the rapid integration of AI tools and technologies in software development lifecycles across multiple industries. The outcomes of this project will aid such industries at the development stage to prevent an accumulation of TD.

Current projects

Our research team currently works on ADEP-704-2024-11481 “A Framework for Detection and Management of Technical Debt in AI projects”. This project consists of several phases. In the initial phase, data collection will be conducted through a survey to identify levels of TD and its management, and the most frequently observed TD types in relation to ISO/IEC 5338:2023 processes will be determined. In the next phase, these relationships between TD and processes will be verified and evaluated by an AI-powered tool. The following phases will focus on developing a TD guideline for practitioners that will utilize the outputs of previous phases.

Our impact

We aim to deliver:

The team

Our team consists of principal investigators (PI) and researchers who are working together to create practical, standards-based frameworks that improve the sustainability and quality of AI software projects.