138 citations · 477 across the 59 of their papers we have counts for
11 papers · 1 filter
Protect Your Secrets: Understanding and Measuring Data Exposure in VSCode Extensions
Yue Liu, Chakkrit Tantithamthavorn, Li Li
Recent years have witnessed the emerging trend of extensions in modern Integrated Development Environments (IDEs) like Visual Studio Code (VSCode) that significantly enhance develo…
MORTAR: Multi-turn Metamorphic Testing for LLM-based Dialogue Systems
Aaron Guoxiang Guo, Aldeida Aleti, Neelofar Neelofar +3
With the widespread application of LLM-based dialogue systems in daily life, quality assurance has become more important than ever. Recent research has successfully introduced meth…
Human-In-the-Loop Software Development Agents
Wannita Takerngsaksiri, Jirat Pasuksmit, Patanamon Thongtanunam +7
Recently, Large Language Models (LLMs)-based multi-agent paradigms for software engineering are introduced to automatically resolve software development tasks (e.g., from a given i…
Code Ownership: The Principles, Differences, and Their Associations with Software Quality
Patanamon Thongtanunam, Chakkrit Tantithamthavorn
Code ownership -- an approximation of the degree of ownership of a software component -- is one of the important software measures used in quality improvement plans. However, prior…
What do AI/ML practitioners think about AI/ML bias?
Aastha Pant, Rashina Hoda, Burak Turhan +1
AI leaders and companies have much to offer to AI/ML practitioners to support them in addressing and mitigating biases in the AI/ML systems they develop. AI/ML practitioners need t…
AI for DevSecOps: A Landscape and Future Opportunities
Michael Fu, Jirat Pasuksmit, Chakkrit Tantithamthavorn
DevOps has emerged as one of the most rapidly evolving software development paradigms. With the growing concerns surrounding security in software systems, the DevSecOps paradigm ha…
Navigating Fairness: Practitioners' Understanding, Challenges, and Strategies in AI/ML Development
Aastha Pant, Rashina Hoda, Chakkrit Tantithamthavorn +1
The rise in the use of AI/ML applications across industries has sparked more discussions about the fairness of AI/ML in recent times. While prior research on the fairness of AI/ML…
Enhancing Large Language Models for Text-to-Testcase Generation
Saranya Alagarsamy, Chakkrit Tantithamthavorn, Wannita Takerngsaksiri +2
Context: Test-driven development (TDD) is a widely employed software development practice that involves developing test cases based on requirements prior to writing the code. Altho…
Practitioners' Challenges and Perceptions of CI Build Failure Predictions at Atlassian
Yang Hong, Chakkrit Tantithamthavorn, Jirat Pasuksmit +4
Continuous Integration (CI) build failures could significantly impact the software development process and teams, such as delaying the release of new features and reducing develope…
Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automation
Chanathip Pornprasit, Chakkrit Tantithamthavorn
Context: The rapid evolution of Large Language Models (LLMs) has sparked significant interest in leveraging their capabilities for automating code review processes. Prior studies o…
PyTester: Deep Reinforcement Learning for Text-to-Testcase Generation
Wannita Takerngsaksiri, Rujikorn Charakorn, Chakkrit Tantithamthavorn +1
Test-driven development (TDD) is a widely-employed software development practice that mandates writing test cases based on requirements before writing the actual code. While writin…