2 citations · 2 across the 6 of their papers we have counts for
8 papers
Ethics Testing: Proactive Identification of Generative AI System Harms
Shin Hwei Tan, Haibo Wang, Heng Li
Generative Artificial Intelligence (GAI) systems that can automatically generate content in the form of source code or other contents (e.g., images) has seen increasing popularity…
Investigating Code Reuse in Software Redesign: A Case Study
Xiaowen Zhang, Huaien Zhang, Shin Hwei Tan
Software redesign preserves functionality while improving quality attributes, but manual reuse of code and tests is costly and error-prone, especially in crossrepository redesigns.…
COBOL-Coder: Domain-Adapted Large Language Models for COBOL Code Generation and Translation
Anh T. V. Dau, Shin Hwei Tan, Jinqiu Yang +2
COBOL remains a critical language for mainframe systems, yet existing large language models (LLMs) struggle to generate and translate COBOL code correctly. This paper reports our e…
COBOLAssist: Analyzing and Fixing Compilation Errors for LLM-Powered COBOL Code Generation
Anh T. V. Dau, Shin Hwei Tan, Jinqiu Yang +2
Legacy programming languages such as COBOL (Common Business-Oriented Language) remain critical in business computing. However, maintaining legacy COBOL systems is increasingly chal…
What Makes Code Generation Ethically Sourced?
Zhuolin Xu, Chenglin Li, Qiushi Li +1
Several code generation models have been proposed to help reduce time and effort in solving software-related tasks. To ensure responsible AI, there are growing interests over vario…
Automated Harmfulness Testing for Code Large Language Models
Honghao Tan, Haibo Wang, Diany Pressato +2
Generative AI systems powered by Large Language Models (LLMs) usually use content moderation to prevent harmful content spread. To evaluate the robustness of content moderation, se…