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20232026
most citedEasy over Hard: A Simple Baseline for Test Failures Causes Prediction

1 citations · 1 across the 15 of their papers we have counts for

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cs.SE2026

Answer Is Cheap, Show Me the Evidence! Augmenting Automated Vulnerability Assessment with Evidence

Shengyi Pan, Zelong Zheng, Jiayuan Zhou +3

Software vulnerability (SV) assessment helps prioritize remediation by characterizing reported vulnerabilities. Existing automated methods predict assessment results from SV report…

cs.SE2026

SmellCC: A Tool for Automated Code Smells Remediation

Xiaoting Zhang, Yujie Zhang, Zhipeng Gao +2

Code smells significantly threaten software maintainability by accumulating technical debt, yet developers often lack the resources to manually address these flaws under tight rele…

cs.SE2026

Automating Just-In-Time Python Type Annotation Updating

Zhipeng Xue, Zhipeng Gao, Xing Hu +3

Type annotations are more and more popular in Python projects to avoid type errors caused by Python's dynamic typing feature. However, when developers change source code, these typ…

cs.SE2026

Refploit: Facilitating Exploit Construction via Code-Agent Trajectory Repair

Zirui Chen, Zhipeng Xue, Jiayuan Zhou +3

Vulnerability exploits play a crucial role in assessing the downstream impact of Java library vulnerabilities. While some vulnerabilities are accompanied by disclosed exploit refer…

cs.SE2026

ATTAIN: Automated Exploit Failure Analysis through Trace-Driven Diff Analysis

Xinwei Mao, Zirui Chen, Xing Hu +1

Exploits are widely used to check whether library vulnerabilities appear in different versions and to mark affected version ranges. Exploit-based checks sometimes fail because expl…

cs.SE2026

An Empirical Study of Speculative Decoding on Software Engineering Tasks

Yijia Li, Junkai Chen, Xing Hu +1

Large Language Models (LLMs) have become widely used for Software Engineering (SE) tasks, spanning from function-level code generation to complex repository-level workflows. Howeve…