6 papers · 1 filter
Can LLMs Reason About Runtime Behavior? A Repository-Level Dynamic Benchmark
Hamed Taherkhani, Mohammad Abdollahi, Melika Sepidband +3
Large language models (LLMs) are increasingly used in coding tasks, but their ability to reason about code execution remains unclear. Existing repository-level QA benchmarks mainly…
On Behavioral Alignment of Model-Code and Human-Code Understandability via Behavioral Proxies
Xiaokai Rong, Aashish Yadavally, Anh H. N. Nguyen +2
Code understandability is a critical aspect of software quality. Prior research has largely focused on this attribute from a human-centric or code-centric perspective, while it sho…
W-RAG: Source-Aware Retrieval for Enterprise Document Generation from Heterogeneous Knowledge Bases
Hridya Dhulipala, Rajesh Ombase, Michael Wang +1
Retrieval-Augmented Generation (RAG) enables large language models to incorporate external knowledge during generation, improving factual grounding and domain adaptability. However…
AdaptAgent: A Multi-agent, Domain-Guided Reasoning Framework for Code Adaptation
Xiaokai Rong, Hridya Dhulipala, Aashish Yadavally +1
Developers often need to adapt into their projects the code generated from LLMs or code snippets from online forums. However, integrating them into an existing repository remains c…
Fuzzwise: Intelligent Initial Corpus Generation for Fuzzing
Hridya Dhulipala, Xiaokai Rong, Aashish Yadavally +1
In mutation-based greybox fuzzing, generating high-quality input seeds for the initial corpus is essential for effective fuzzing. Rather than conducting separate phases for generat…
Cerberus: Multi-Agent Reasoning and Coverage-Guided Exploration for Static Detection of Runtime Errors
Hridya Dhulipala, Xiaokai Rong, Tien N. Nguyen
In several software development scenarios, it is desirable to detect runtime errors and exceptions in code snippets without actual execution. A typical example is to detect runtime…