OPAL中的模块化协同程序分析
Modular Collaborative Program Analysis in OPAL
摘要：
目前的方法结合了多个静态分析，得出不同的，独立的属性集中在模块化或性能。声明式方法促进模块化和自动化，独立于分析的优化，而命令式方法促进手动，特定于分析的优化。在本文中，我们提出了一种新的方法来静态分析，利用黑板系统的模块化，并结合声明和命令式技术。我们的方法允许可交换性和可插拔扩展的分析，以提高健全性，精度和可扩展性，并明确地使否则不兼容的分析的组合。通过将我们的方法集成到OPAL框架中，我们能够实现各种不同的分析，包括比Doop（最先进的点分析框架）的等效分析性能更好的点分析。
英文摘要：
Current approaches combining multiple static analyses deriving different, independent properties focus either on modularity or performance. Whereas declarative approaches facilitate modularity and automated, analysis-independent optimizations, imperative approaches foster manual, analysis-specific optimizations. In this paper, we present a novel approach to static analyses that leverages the modularity of blackboard systems and combines declarative and imperative techniques. Our approach allows exchangeability, and pluggable extension of analyses in order to improve sound(i)ness, precision, and scalability and explicitly enables the combination of otherwise incompatible analyses. With our approach integrated in the OPAL framework, we were able to implement various dissimilar analyses, including a points-to analysis that outperforms an equivalent analysis from Doop, the state-of-the-art points-to analysis framework.
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