金山云：附属公司拟以5000万元收购网心科技20%股权
Abstract:Large language model (LLM)-powered agents have demonstrated strong capabilities in automating software engineering tasks such as static bug fixing, as evidenced by benchmarks like SWE-bench. However, in the real world, the development of mature software is typically predicated on complex requirement changes and long-term feature iterations -- a process that static, one-shot repair paradigms fail to capture. To bridge this gap, we propose \textbf{SWE-CI}, the first repository-level benchmark built upon the Continuous Integration loop, aiming to shift the evaluation paradigm for code generation from static, short-term \textit{functional correctness} toward dynamic, long-term \textit{maintainability}. The benchmark comprises 100 tasks, each corresponding on average to an evolution history spanning 233 days and 71 consecutive commits in a real-world code repository. SWE-CI requires agents to systematically resolve these tasks through dozens of rounds of analysis and coding iterations. SWE-CI provides valuable insights into how well agents can sustain code quality throughout long-term evolution.
。关于这个话题，safew提供了深入分析
Раскрыты подробности похищения ребенка в Смоленске09:27
五、那只最贵的虾，可能正在删你的库评测最后，必须把安全提到最高优先级。，推荐阅读传奇私服新开网｜热血传奇SF发布站｜传奇私服网站获取更多信息
Марина Совина (ночной редактор)
ВВС США купят броневики для ядерных «Минитменов»02:00，详情可参考今日热点