CAREER: A Framework For Customizable Program Flow Analysis

CCF-0642911 CAREER：可定制程序流分析的框架Ana Milanova今天的软件系统是大型、复杂和昂贵的，程序流分析对软件生产率和软件质量的研究越来越重要。基于流分析的工具可以帮助和改进软件任务，如开发、测试、程序理解、验证、调试、逆向工程和重构。这项研究构建的技术将允许指定和开发支持大型和复杂软件系统上的软件任务的定制流分析。有三个贡献。首先，我们开发了上下文集合约束理论，这是一种用于指定流分析的灵活的声明性形式主义。其次，我们设计并实现了一种新的集合约束解析引擎，该引擎利用高效的二叉决策图(BDD)技术进行集合表示和集合操作。第三，构建了一个基于上下文集合约束和高效约束解析的分析框架。该框架用于指定和开发新的流程分析，以解决与软件安全和软件可靠性相关的长期存在的问题。

CCF-0642911CAREER: A Framework for Customizable Program Flow AnalysisAna MilanovaToday's software systems are large, complex and costly and research on program flow analysis for software productivity and software quality is increasingly relevant. Tools based on flow analysis can aid and improve software tasks such as development, testing, program understanding, verification, debugging, reverse engineering, and restructuring. This wide variety of tasks demands a wide variety of customized flow analyses with different degrees of precision and cost.This research builds technology that will allow specifying and developing customized flow analyses that support software tasks on large and complex software systems. There are three contributions. First, we develop the theory of contextual set constraints, a flexible declarative formalism for specifying flow analyses. Second, we design and implement a novel engine for resolution of set constraint which takes advantage of efficient Binary Decision Diagram (BDD) technology for set representation and set manipulation. Third, we build an analysis framework based on contextual set constraints and efficient constraint resolution. The framework is used to specify and develop new flow analyses that target long-standing problems related to software security and software dependability.