138 citations · 477 across the 59 of their papers we have counts for
16 papers · 1 filter
When AI Takes the Wheel: Security Analysis of Framework-Constrained Program Generation
Yue Liu, Zhenchang Xing, Shidong Pan +1
In recent years, the AI wave has grown rapidly in software development. Even novice developers can now design and generate complex framework-constrained software systems based on t…
What Types of Code Review Comments Do Developers Most Frequently Resolve?
Saul Goldman, Hong Yi Lin, Jirat Pasuksmit +11
Large language model (LLM)-powered code review automation tools have been introduced to generate code review comments. However, not all generated comments will drive code changes.…
DecipherGuard: Understanding and Deciphering Jailbreak Prompts for a Safer Deployment of Intelligent Software Systems
Rui Yang, Michael Fu, Chakkrit Tantithamthavorn +3
Intelligent software systems powered by Large Language Models (LLMs) are increasingly deployed in critical sectors, raising concerns about their safety during runtime. Through an i…
AdaptiveGuard: Towards Adaptive Runtime Safety for LLM-Powered Software
Rui Yang, Michael Fu, Chakkrit Tantithamthavorn +3
Guardrails are critical for the safe deployment of Large Language Models (LLMs)-powered software. Unlike traditional rule-based systems with limited, predefined input-output spaces…
Multi-Modal Requirements Data-based Acceptance Criteria Generation using LLMs
Fanyu Wang, Chetan Arora, Yonghui Liu +5
Acceptance criteria (ACs) play a critical role in software development by clearly defining the conditions under which a software feature satisfies stakeholder expectations. However…
On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
Dong wang, Junji Yu, Honglin Shu +4
Various Deep Learning-based approaches with pre-trained language models have been proposed for automatically repairing software vulnerabilities. However, these approaches are limit…
SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for LLM Software Systems
Wenliang Shan, Michael Fu, Rui Yang +1
Safety alignment is critical for LLM-powered systems. While recent LLM-powered guardrail approaches such as LlamaGuard achieve high detection accuracy of unsafe inputs written in E…
From Domain Documents to Requirements: Retrieval-Augmented Generation in the Space Industry
Chetan Arora, Fanyu Wang, Chakkrit Tantithamthavorn +2
Requirements engineering (RE) in the space industry is inherently complex, demanding high precision, alignment with rigorous standards, and adaptability to mission-specific constra…
Human-In-The-Loop Software Development Agents: Challenges and Future Directions
Jirat Pasuksmit, Wannita Takerngsaksiri, Patanamon Thongtanunam +8
Multi-agent LLM-driven systems for software development are rapidly gaining traction, offering new opportunities to enhance productivity. At Atlassian, we deployed Human-in-the-Loo…
Evaluating Large Language Models for Multilingual Vulnerability Detection at Dual Granularities
Honglin Shu, Michael Fu, Junji Yu +4
Various deep learning-based approaches utilizing pre-trained language models (PLMs) have been proposed for automated vulnerability detection. With recent advancements in large lang…
A Preliminary Study of Large Language Models for Multilingual Vulnerability Detection
Junji Yu, Honglin Shu, Michael Fu +4
Deep learning-based approaches, particularly those leveraging pre-trained language models (PLMs), have shown promise in automated software vulnerability detection. However, existin…
Blended PC Peer Review Model: Process and Reflection
Chakkrit Tantithamthavorn, Nicole Novielli, Ayushi Rastogi +2
The academic peer review system is under increasing pressure due to a growing volume of submissions and a limited pool of available reviewers, resulting in delayed decisions and an…
RAGVA: Engineering Retrieval Augmented Generation-based Virtual Assistants in Practice
Rui Yang, Michael Fu, Chakkrit Tantithamthavorn +3
Retrieval-augmented generation (RAG)-based applications are gaining prominence due to their ability to leverage large language models (LLMs). These systems excel at combining retri…
Requirements-Driven Automated Software Testing: A Systematic Review
Fanyu Wang, Chetan Arora, Chakkrit Tantithamthavorn +2
Automated software testing has significant potential to enhance efficiency and reliability within software development processes. However, its broader adoption faces considerable c…
Comparing Human and LLM Generated Code: The Jury is Still Out!
Sherlock A. Licorish, Ansh Bajpai, Chetan Arora +2
Much is promised in relation to AI-supported software development. However, there has been limited evaluation effort in the research domain aimed at validating the true utility of…
Code Readability in the Age of Large Language Models: An Industrial Case Study from Atlassian
Wannita Takerngsaksiri, Chakkrit Tantithamthavorn, Micheal Fu +3
Software engineers spend a significant amount of time reading code during the software development process, especially in the age of large language models (LLMs) that can automatic…