AutoDev: Automated AI-Driven Development

no code implementations • 13 Mar 2024 • Michele Tufano, Anisha Agarwal, Jinu Jang, Roshanak Zilouchian Moghaddam, Neel Sundaresan

This enables the AI Agents to execute tasks in a fully automated manner with a comprehensive understanding of the contextual information required.

Code Generation

Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming

no code implementations • 22 Feb 2024 • Anisha Agarwal, Aaron Chan, Shubham Chandel, Jinu Jang, Shaun Miller, Roshanak Zilouchian Moghaddam, Yevhen Mohylevskyy, Neel Sundaresan, Michele Tufano

The integration of Large Language Models (LLMs) into Development Environments (IDEs) has become a focal point in modern software development.

Bug fixing Code Generation

Predicting Code Coverage without Execution

1 code implementation • 25 Jul 2023 • Michele Tufano, Shubham Chandel, Anisha Agarwal, Neel Sundaresan, Colin Clement

Using Machine Learning to amortize this expensive process could lower the cost of code coverage by requiring only the source code context, and the task of code coverage prediction can be a novel benchmark for judging the ability of models to understand code.

Protecting Privacy of Users in Brain-Computer Interface Applications

no code implementations • 2 Jul 2019 • Anisha Agarwal, Rafael Dowsley, Nicholas D. McKinney, Dongrui Wu, Chin-Teng Lin, Martine De Cock, Anderson C. A. Nascimento

Machine learning (ML) is revolutionizing research and industry.

Brain Computer Interface EEG +1