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

AdaptivePaste: Code Adaptation through Learning Semantics-aware Variable Usage Representations

no code implementations • 23 May 2022 • Xiaoyu Liu, Jinu Jang, Neel Sundaresan, Miltiadis Allamanis, Alexey Svyatkovskiy

This scenario motivates the code adaptation task -- a variant of program repair which aims to adapt variable identifiers in a pasted snippet of code to the surrounding, preexisting source code.

Program Repair

Program Merge Conflict Resolution via Neural Transformers

1 code implementation • 31 Aug 2021 • Alexey Svyatkovskiy, Sarah Fakhoury, Negar Ghorbani, Todd Mytkowicz, Elizabeth Dinella, Christian Bird, Jinu Jang, Neel Sundaresan, Shuvendu Lahiri

Our model achieves 63-68% accuracy for merge resolution synthesis, yielding nearly a 3x performance improvement over existing semi-structured, and 2x improvement over neural program merge tools.