Rethinking Soot for Summary-Based Whole-Program Analysis

Whole-program static analysis has been extensively studied and widely used in the past few decades. For modern object-oriented programs, scalability has become an important issue for using whole-program analysis in real-world tools. In addition, the ever-increasing size of libraries (e.g., the JDK library) and frameworks exacerbates the scalability problems. To achieve the desired level of analysis performance, an effective approach could be to gener-ate and apply analysis summary information for library methods. In this paper, such an approach is referred to as a summary-based whole-program analysis. The challenges for this technique are two-fold: (1) carefully designed abstractions and algorithms are needed to create and use client-independent and analysis-specific library summary information; and (2) support for summary generation and application should be effectively incorporated into existing analysis infrastructures. This paper focuses on the second challenge. It uses Soot, a widely-used program analysis framework for Java, as a vehicle to explore some of the important issues in providing analysis in-frastructures with capabilities for summary-based analysis. Exper-imental studies are presented to show that significant savings can potentially be achieved by making a whole-program alias analysis summary-based. To actually achieve these savings, the paper pro-poses to extend Soot to add support for summary-based analysis. Finally, a brief discussion of the required framework extensions is presented