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20232026
most citedRevisiting Code Similarity Evaluation with Abstract Syntax Tree Edit Distance

15 citations · 28 across the 22 of their papers we have counts for

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10 papers · 1 filter

cs.SE2026

Memorization Diagnostics for Code LLMs Should be Scale-Aware

Prateek Kumar Rajput, Abdoul Aziz Bonkoungou, Alberick Euraste Djiré +6

The extent to which large language models for code rely on memorization over genuine understanding remains highly debated. While current literature frequently reports widespread me…

cs.SE2026

Empirical Study for Structured Output Control in LLMs for Software Engineering

Yewei Song, Prateek Rajput, Tiezhu Sun +3

LLM-generated outputs in software engineering rarely exist in isolation. They must plug into toolchains, APIs, and data pipelines that impose strict, often organization-specific st…

cs.SE2026

Correctness isnt Efficiency: Runtime Memory Divergence in LLM-Generated Code

Prateek Rajput, Yewei Song, Abdoul Aziz Bonkoungou +4

Large language models (LLMs) can generate programs that pass unit tests, but passing tests does not guarantee reliable runtime behavior. We find that different correct solutions to…

cs.SE2025

Measuring LLM Code Generation Stability via Structural Entropy

Yewei Song, Tiezhu Sun, Xunzhu Tang +3

Assessing the stability of code generation from large language models (LLMs) is essential for judging their reliability in real-world development. We extend prior "structural-entro…

cs.SE2025

CallNavi, A Challenge and Empirical Study on LLM Function Calling and Routing

Yewei Song, Xunzhu Tang, Cedric Lothritz +6

API-driven chatbot systems are increasingly integral to software engineering applications, yet their effectiveness hinges on accurately generating and executing API calls. This is…

cs.SE2024★ 5 cited

Large-scale, Independent and Comprehensive study of the power of LLMs for test case generation

Wendkûuni C. Ouédraogo, Kader Kaboré, Yinghua Li +5

Unit testing is essential for software reliability, yet manual test creation is time-consuming and often neglected. Search-based software testing improves efficiency but produces t…

cs.SE2024★ 3 cited

CodeAgent: Autonomous Communicative Agents for Code Review

Xunzhu Tang, Kisub Kim, Yewei Song +6

Code review, which aims at ensuring the overall quality and reliability of software, is a cornerstone of software development. Unfortunately, while crucial, Code review is a labor-…

cs.SE2024

Enhancing Text-to-SQL Translation for Financial System Design

Yewei Song, Saad Ezzini, Xunzhu Tang +6

Text-to-SQL, the task of translating natural language questions into SQL queries, is part of various business processes. Its automation, which is an emerging challenge, will empowe…

cs.SE2023★ 2 cited

Hyperbolic Code Retrieval: A Novel Approach for Efficient Code Search Using Hyperbolic Space Embeddings

Xunzhu Tang, zhenghan Chen, Saad Ezzini +4

Within the realm of advanced code retrieval, existing methods have primarily relied on intricate matching and attention-based mechanisms. However, these methods often lead to compu…

cs.SE2023★ 2 cited

Multilevel Semantic Embedding of Software Patches: A Fine-to-Coarse Grained Approach Towards Security Patch Detection

Xunzhu Tang, zhenghan Chen, Saad Ezzini +4

The growth of open-source software has increased the risk of hidden vulnerabilities that can affect downstream software applications. This concern is further exacerbated by softwar…