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    A recommendation system for predicting dependencies among software changes insights from an empirical study on OpenStack

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    Open source software development tool installation

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    Multi-scenario benchmark for autonomous driving systems: Exposing diverse behavioral anomalies

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    : ntrastive Learning for Autoated tch Correctness Aessment in Program Repair

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    Identifying performance-sensitive configurations in software systems with LLM-based agents

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    From brittle to robust: Improving LLM annotations for SE optimization

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    Understanding developer well-being: measuring mental health and productivity in software teams

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    Plug it and Play on Logs: A configuration-free statistic-based log parser

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    Exploring and improving knowledge distillation for pre-trained code models

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    CMF-Vul: Advancing automated vulnerability detection via contrastive multimodal fusion and challenge-driven representation learning

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    Effective Fine-tuning for Low-resource Languages: A Case Study of Cangjie

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    Machine learning, deep learning, or large language models: An empirical study on multi-label requirements classification

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    Is this build failure related to my patch? An empirical study of unrelated build failures in continuous integration

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    A multi-language perspective on the robustness of LLM code generation

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    On the emergence of testing strategies: A socio-technical grounded theory

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    HypeAssign: Hypergraph contrastive learning for issue assignment

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    Meta-enhanced code: leveraging structural and functional features for precise cross-modal code search

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    An empirical analysis of vulnerability detection tools for solidity smart contracts

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    PRaFFLineDP: Feature fusion with progressive ranking for efficient line-level defect prediction

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    An empirical evaluation of white-box and black-box test case prioritization techniques in CPSs modeled in Simulink

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