数据流引导切片

摘要：

我们提出了一个流不敏感的分析，修剪出部分的代码是不相关的一组指定的数据流路径。我们的方法快速且可扩展，此外还能够生成证书作为计算结果的审计。我们已经在一个名为DSlicer的工具中实现了我们的技术，并将其应用于一组10600个真实的Android应用程序。结果是结论性的，我们发现，相对于一组指定的数据泄漏路径，程序代码平均可以显著减少36%。

英文摘要：

We propose a flow-insensitive analysis that prunes out portions of code which are irrelevant to a specified set of data-flow paths. Our approach is fast and scalable, in addition to being able to generate a certificate as an audit for the computed result. We have implemented our technique in a tool called DSlicer and applied it to a set of 10600 real-world Android applications. Results are conclusive, we found out that the program code can be significantly reduced by 36% on average with respect to a specified set of data leak paths.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。