Collaborative agents for software engineering

D Tang, Z Chen, K Kim, Y Song, H Tian… - arxiv e …, 2024 - ui.adsabs.harvard.edu
Code review is a heavily collaborative process, which aims at ensuring the overall quality
and reliability of software. While it provides massive benefits, the implementation of code …

Advanced large language models and visualization tools for data analytics learning

J Valverde-Rebaza, A González… - Frontiers in …, 2024 - frontiersin.org
Introduction In recent years, numerous AI tools have been employed to equip learners with
diverse technical skills such as coding, data analysis, and other competencies related to …

Bridging design and development with automated declarative ui code generation

T Zhou, Y Zhao, X Hou, X Sun, K Chen… - arxiv preprint arxiv …, 2024 - arxiv.org
Declarative UI frameworks have gained widespread adoption in mobile app development,
offering benefits such as improved code readability and easier maintenance. Despite these …

CodeAgent: Autonomous Communicative Agents for Code Review

X Tang, K Kim, Y Song, C Lothritz, B Li… - Proceedings of the …, 2024 - aclanthology.org
Code review, which aims at ensuring the overall quality and reliability of software, is a
cornerstone of software development. Unfortunately, while crucial, Code review is a labor …

Swe-bench+: Enhanced coding benchmark for llms

R Aleithan, H Xue, MM Mohajer, E Nnorom… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) in Software Engineering (SE) can offer assistance for
coding. To facilitate a rigorous evaluation of LLMs in practical coding contexts, Carlos et al …

GPT-4 as a homework tutor can improve student engagement and learning outcomes

A Vanzo, SP Chowdhury, M Sachan - arxiv preprint arxiv:2409.15981, 2024 - arxiv.org
This work contributes to the scarce empirical literature on LLM-based interactive homework
in real-world educational settings and offers a practical, scalable solution for improving …

You Don't Have to Say Where to Edit! jLED–Joint Learning to Localize and Edit Source Code

W Pian, Y Li, H Tian, T Sun, Y Song, X Tang… - ACM Transactions on …, 2025 - dl.acm.org
Learning to edit code automatically is becoming more and more feasible. Thanks to recent
advances in Neural Machine Translation (NMT), various case studies are being investigated …

When Fine-Tuning LLMs Meets Data Privacy: An Empirical Study of Federated Learning in LLM-Based Program Repair

W Luo, JW Keung, B Yang, H Ye, CL Goues… - arxiv preprint arxiv …, 2024 - arxiv.org
Software systems have been evolving rapidly and inevitably introducing bugs at an
increasing rate, leading to significant losses in resources consumed by software …

Detecting Multi-Parameter Constraint Inconsistencies in Python Data Science Libraries

X Xu, F **e, C Zhu, G Bai, S Khurshid, Y Li - arxiv preprint arxiv …, 2024 - arxiv.org
Modern AI-and Data-intensive software systems rely heavily on data science and machine
learning libraries that provide essential algorithmic implementations and computational …

Integrating Various Software Artifacts for Better LLM-based Bug Localization and Program Repair

Q Feng, X Ma, J Sheng, Z Feng, W Song… - arxiv preprint arxiv …, 2024 - arxiv.org
LLMs have garnered considerable attention for their potential to streamline Automated
Program Repair (APR). LLM-based approaches can either insert the correct code or directly …