Salsa:序列化特征的静态分析

Joanna C. S. Santos, Reese A. Jones, Mehdi Mirakhorli
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引用次数: 2

摘要

静态分析具有对多个可能路径进行推理的优势。因此,它已被广泛用于程序属性的验证。属性验证通常需要过程间分析,其中跨方法跟踪控制和数据流。过程间分析的核心是调用图,它建立了调用方和被调用方方法之间的关系。然而,对具有动态特征的程序进行静态分析和计算调用图是一项挑战。动态特性在软件系统中应用广泛;如果不支持这些特性,就很难推断出与这些特性相关的属性。尽管最先进的研究已经探索了某些类型的动态特征,如反射和基于rmi的程序,但序列化相关的特征仍然没有得到很好的支持,正如最近的一项实证研究所证明的那样。因此,在本文中,我们引入了Salsa(序列化特性静态分析器),它旨在增强与序列化相关特性相关的现有点分析。目标是增强生成的调用图的稳健性,同时不会对其精度产生太大影响。在本文中,我们报告了我们在开发Salsa方面的早期工作,以及使用Java调用图测试套件(JCG)对其进行的早期评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Salsa: static analysis of serialization features
Static analysis has the advantage of reasoning over multiple possible paths. Thus, it has been widely used for verification of program properties. Property verification often requires inter-procedural analysis, in which control and data flow are tracked across methods. At the core of inter-procedural analyses is the call graph, which establishes relationships between caller and callee methods. However, it is challenging to perform static analysis and compute the call graph of programs with dynamic features. Dynamic features are widely used in software systems; not supporting them makes it difficult to reason over properties related to these features. Although state-of-the-art research had explored certain types of dynamic features, such as reflection and RMI-based programs, serialization-related features are still not very well supported, as demonstrated in a recent empirical study. Therefore, in this paper, we introduce Salsa (Static AnaLyzer for SeriAlization features), which aims to enhance existing points-to analysis with respect to serialization-related features. The goal is to enhance the resulting call graph's soundness, while not greatly affecting its precision. In this paper, we report our early effort in developing Salsa and its early evaluation using the Java Call Graph Test Suite (JCG).
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