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#reinforcement learning Open access Oct 2026

From Greedy Steps to Global Optimization: Learning Sequential Test Suite Generation

This paper formalizes test suite generation as a Markov Decision Process (MDP) and demonstrates that its objective exhibits monotone submodularity, which enables an effective relaxation of this NP-hard global optimization into a tractable step-wise greedy procedure.

Guo-Qing Wang, Cheng-Ran Yang, Xiao-Xuan Zhou et al. · 0 citations
#large language models Open access Oct 2026

Contamination Means Overestimation? A Fine-Grained Empirical Study in Code Intelligence

In recent years, code intelligence has gained increasing importance in the field of automated software engineering. Meanwhile, the widespread adoption of Pretrained Language Models (PLMs) and Large Language Models (LLMs) has raised concerns regarding data contamination and its potential impact on model performance eval...

Zhen Chuan Yang, Hongyi Lin, Yifan He et al. · 0 citations

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