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GFTrans:用于代码性能分析的随时静态分析框架
Jie Li1, Yunbao Wen1, Jingxin Liu2
1School of Artificial Intelligence, South China Normal University, Foshan, China.
Frontiers in big data
|March 16, 2026
概括
GFTrans是一个新的静态分析框架,可以在没有运行代码的情况下预测C程序的性能. 这个工具可以帮助开发人员在编码阶段快速识别软件瓶,提高效率.
科学领域:
- 计算机科学 计算机科学
- 软件工程 软件工程 软件工程
- 人工智能的人工智能
背景情况:
- 软件效率对于系统维护和性能至关重要.
- 在大型,复杂的系统中识别运行时瓶是具有挑战性的.
- 传统的动态分析方法引入了显著的延迟,阻碍了敏捷开发.
研究的目的:
- 介绍GFTrans,这是一个用于预测C程序性能的新型静态分析框架.
- 为了使开发人员能够在开发周期的早期识别性能瓶,而无需执行代码.
主要方法:
- 开发了GFTrans,这是一个使用变压器架构的静态分析框架.
- 实施了一种"基于嵌"的技术,以集成控制流和数据依赖.
- 整合了一个动态门机制,以将语义表示与手工制作的统计特征融合在一起.
主要成果:
- 在真实世界C函数的数据集上,GFTrans实现了78.64%的准确性.
- 超越了基线模型的表现,例如随机森林和Code2Vec.
- 在毫秒内确定了潜在的性能瓶.
结论:
- 通过静态分析,GFTrans为预测C程序性能提供了有效的解决方案.
- 该框架显著减少了与瓶识别相关的延迟时间.
- 允许开发人员在开发阶段主动优化代码.
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