贝叶斯程序分析  

Bayesian Program Analysis

作　　者：张昕 王冠成 吴宜谦 陈逸凡 李天驰 张羿凡 熊英飞 ZHANG Xin;WANG Guan-cheng;WU Yi-qian;CHEN Yi-fan;LI Tian-chi;ZHANG Yi-fan;XIONG Ying-fei(Key Laboratory of High Confidence Software Technologies(Peking University),Ministry of Education,Beijing 100871,China;School of Computer Science,Peking University,Beijing 100871,China)

机构地区：[1]高可信软件技术教育部重点实验室(北京大学),北京100871 [2]北京大学计算机学院,北京100871

出　　处：《电子学报》2024年第4期1155-1172,共18页Acta Electronica Sinica

基　　金：国家重点研发计划(No.2022YFB4501902);国家自然科学基金(No.62172017)。

摘　　要：程序分析在软件开发和维护中发挥着关键作用.然而,传统基于逻辑的程序分析方法在处理现代复杂、大规模和动态特性丰富的软件系统时往往效果有限,其根源在于软件系统中的不确定性.研究人员针对具体的程序分析问题提出了一系列新的技术,其特征是在传统逻辑分析的基础上结合概率信息来捕获软件系统中的不确定性.通过总结和抽象这些已有工作,本文提出了贝叶斯程序分析框架,其核心思想是结合程序分析和贝叶斯统计推断,通过建模和更新关于程序的概率分布来推断有关程序行为的信息.贝叶斯程序分析采用概率逻辑编程来同时处理概率信息和逻辑信息,用统一的方式捕获了现有的多项不同工作,也能泛化到程序缺陷定位和差异调试等非传统程序静态分析任务上.本文给出了贝叶斯程序分析框架的定义,展示了该框架在程序分析和相关领域的应用,并展望了未来发展方向.ing existing work in this area,this paper introduces the Bayesian program analysis framework.The core idea of this framework is to integrate program analysis with Bayesian statistical inference.It does so by modeling and updating probability distributions about the program to infer information about program behavior.Bayes⁃ian program analysis employs probabilistic logic programming to simultaneously handle both probability and logic informa⁃tion,providing a unified approach that encompasses various existing works.It can also be generalized to non-traditional static program analysis tasks,such as program fault localization and delta debugging.This paper provides a definition of the Bayesian program analysis framework,demonstrates its applications in program analysis and related fields,and outlines future directions for development.

关 键 词：程序分析 逻辑编程 概率逻辑编程 贝叶斯网络 贝叶斯推断 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]