Automatically Estimating the Effort Required to Repay Self-Admitted Technical Debt

1 code implementation • 12 Sep 2023 • Yikun Li, Mohamed Soliman, Paris Avgeriou

Technical debt refers to the consequences of sub-optimal decisions made during software development that prioritize short-term benefits over long-term maintainability.

Automatically Identifying Relations Between Self-Admitted Technical Debt Across Different Sources

1 code implementation • 13 Mar 2023 • Yikun Li, Mohamed Soliman, Paris Avgeriou

Self-Admitted Technical Debt or SATD can be found in various sources, such as source code comments, commit messages, issue tracking systems, and pull requests.

Management

Automatic Identification of Self-Admitted Technical Debt from Four Different Sources

1 code implementation • 4 Feb 2022 • Yikun Li, Mohamed Soliman, Paris Avgeriou

Therefore, we propose and evaluate an approach for automated SATD identification that integrates four sources: source code comments, commit messages, pull requests, and issue tracking systems.

Identifying Self-Admitted Technical Debt in Issue Tracking Systems using Machine Learning

1 code implementation • 4 Feb 2022 • Yikun Li, Mohamed Soliman, Paris Avgeriou

In addition to source code comments, issue tracking systems have shown to be another rich source of SATD, but there are no approaches specifically for automatically identifying SATD in issues.

BIG-bench Machine Learning

Learning to Grasp 3D Objects using Deep Residual U-Nets

1 code implementation • 10 Feb 2020 • Yikun Li, Lambert Schomaker, S. Hamidreza Kasaei

Affordance detection is one of the challenging tasks in robotics because it must predict the grasp configuration for the object of interest in real-time to enable the robot to interact with the environment.

Robotics