9 papers · 1 filter
HEJ-Robust: A Robustness Benchmark for LLM-Based Automated Program Repair
Fazle Rabbi, Jinqiu Yang
Recent Large Language Models (LLMs) have shown strong performance on automated program repair across standard benchmarks. However, these benchmarks evaluate models on a single cano…
Beyond Translation Accuracy: Addressing False Failures in LLM-Based Code Translation
Fazle Rabbi, Soumit Kanti Saha, Jinqiu Yang
Large Language Models (LLMs) have achieved remarkable success in automated code translation. While prior work has focused on improving translation accuracy through advanced prompti…
Social Bias in LLM-Generated Code: Benchmark and Mitigation
Fazle Rabbi, Lin Ling, Song Wang +1
Large Language Models (LLMs) are increasingly deployed to generate code for human-centered applications where demographic fairness is critical. However, existing evaluations focus…
BabelCoder: Agentic Code Translation with Specification Alignment
Fazle Rabbi, Soumit Kanti Saha, Tri Minh Triet Pham +2
As software systems evolve, developers increasingly work across multiple programming languages and often face the need to migrate code from one language to another. While automatic…
Secure-Instruct: An Automated Pipeline for Synthesizing Instruction-Tuning Datasets Using LLMs for Secure Code Generation
Junjie Li, Fazle Rabbi, Bo Yang +2
Although Large Language Models (LLMs) show promising solutions to automated code generation, they often produce insecure code that threatens software security. Current approaches (…
A Multi-Language Perspective on the Robustness of LLM Code Generation
Fazle Rabbi, Zishuo Ding, Jinqiu Yang
Large language models have gained significant traction and popularity in recent times, extending their usage to code-generation tasks. While this field has garnered considerable at…
Specification-Driven Code Translation Powered by Large Language Models: How Far Are We?
Soumit Kanti Saha, Fazle Rabbi, Song Wang +1
Large Language Models (LLMs) are increasingly being applied across various domains, including code-related tasks such as code translation. Previous studies have explored using LLMs…
Bias Unveiled: Investigating Social Bias in LLM-Generated Code
Lin Ling, Fazle Rabbi, Song Wang +1
Large language models (LLMs) have significantly advanced the field of automated code generation. However, a notable research gap exists in evaluating social biases that may be pres…
An Exploratory Study on Fine-Tuning Large Language Models for Secure Code Generation
Junjie Li, Fazle Rabbi, Cheng Cheng +3
AI-powered coding assistants such as GitHub's Copilot and OpenAI's ChatGPT have achieved notable success in automating code generation. However, these tools rely on pre-trained Lar…