27 citations · 45 across the 32 of their papers we have counts for
8 papers · 1 filter
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…
CFCEval: Evaluating Security Aspects in Code Generated by Large Language Models
Cheng Cheng, Jinqiu Yang
Code-focused Large Language Models (LLMs), such as CodeX and Star-Coder, have demonstrated remarkable capabilities in enhancing developer productivity through context-aware code ge…
Demystifying Errors in LLM Reasoning Traces: An Empirical Study of Code Execution Simulation
Mohammad Abdollahi, Khandaker Rifah Tasnia, Soumit Kanti Saha +3
Understanding a program's runtime reasoning behavior, meaning how intermediate states and control flows lead to final execution results, is essential for reliable code generation,…
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 (…
ADPerf: Investigating and Testing Performance in Autonomous Driving Systems
Tri Minh-Triet Pham, Diego Elias Costa, Weiyi Shang +1
Obstacle detection is crucial to the operation of autonomous driving systems, which rely on multiple sensors, such as cameras and LiDARs, combined with code logic and deep learning…
RobuNFR: Evaluating the Robustness of Large Language Models on Non-Functional Requirements Aware Code Generation
Feng Lin, Dong Jae Kim, Zhenhao Li +3
When using LLMs to address Non-Functional Requirements (NFRs), developers may behave differently (e.g., expressing the same NFR in different words). Robust LLMs should output consi…
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…
MANTRA: Enhancing Automated Method-Level Refactoring with Contextual RAG and Multi-Agent LLM Collaboration
Yisen Xu, Feng Lin, Jinqiu Yang +3
Maintaining and scaling software systems relies heavily on effective code refactoring, yet this process remains labor-intensive, requiring developers to carefully analyze existing…