11 citations · 47 across the 12 of their papers we have counts for
12 papers
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…
Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey
Xinyu She, Yue Liu, Yanjie Zhao +5
Modern language models (LMs) have been successfully employed in source code generation and understanding, leading to a significant increase in research focused on learning-based co…
ChatGPT for Vulnerability Detection, Classification, and Repair: How Far Are We?
Michael Fu, Chakkrit Tantithamthavorn, Van Nguyen +1
Large language models (LLMs) like ChatGPT (i.e., gpt-3.5-turbo and gpt-4) exhibited remarkable advancement in a range of software engineering tasks associated with source code such…
Unit Testing Challenges with Automated Marking
Chakkrit Tantithamthavorn, Norman Chen
Teaching software testing presents difficulties due to its abstract and conceptual nature. The lack of tangible outcomes and limited emphasis on hands-on experience further compoun…