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Eventually Sound Points-To Analysis with Specifications

机译:最终通过技术指标进行声音指向分析

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Static analyses make the increasingly tenuous assumption that all source code is available for analysis; for example, large libraries often call into native code that cannot be analyzed. We propose a points-to analysis that initially makes optimistic assumptions about missing code, and then inserts runtime checks that report counterexamples to these assumptions that occur during execution. Our approach guarantees eventual soundness, which combines two guarantees: (i) the runtime checks are guaranteed to catch the first counterexample that occurs during any execution, in which case execution can be terminated to prevent harm, and (ii) only finitely many counterexamples ever occur, implying that the static analysis eventually becomes statically sound with respect to all remaining executions. We implement Optix, an eventually sound points-to analysis for Android apps, where the Android framework is missing. We show that the runtime checks added by Optix incur low overhead on real programs, and demonstrate how Optix improves a client information flow analysis for detecting Android malware.
机译:静态分析越来越狭assumption地假设所有源代码都可用于分析。例如,大型库经常调用无法分析的本机代码。我们提出了一个指向分析,该分析首先对丢失的代码做出乐观的假设,然后插入运行时检查,以报告与执行期间发生的这些假设的反例。我们的方法保证了最终的健全性,它结合了两个保证:(i)确保运行时检查能够捕获在任何执行期间发生的第一个反例,在这种情况下可以终止执行以防止损害;(ii)仅有限地有多个反例发生,意味着静态分析最终相对于所有其余执行静态变为合理。我们实施Optix,这是缺少Android框架的Android应用程序的最终指向分析。我们证明了Optix添加的运行时检查在真实程序上的开销较低,并展示了Optix如何改进用于检测Android恶意软件的客户端信息流分析。

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