Fast static analysis of C++ virtual function calls

Author:

Bacon David F.1,Sweeney Peter F.1

Affiliation:

1. IBM Watson Research Center, P.O. Box 704, Yorktown Heights, NY

Abstract

Virtual functions make code easier for programmers to reuse but also make it harder for compilers to analyze. We investigate the ability of three static analysis algorithms to improve C++ programs by resolving virtual function calls, thereby reducing compiled code size and reducing program complexity so as to improve both human and automated program understanding and analysis. In measurements of seven programs of significant size (5000 to 20000 lines of code each) we found that on average the most precise of the three algorithms resolved 71% of the virtual function calls and reduced compiled code size by 25%. This algorithm is very fast: it analyzes 3300 source lines per second on an 80 MHz PowerPC 601. Because of its accuracy and speed, this algorithm is an excellent candidate for inclusion in production C++ compilers.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 140 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Characterizing and Detecting Program Representation Faults of Static Analysis Frameworks;Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis;2024-09-11

2. Scaling Type-Based Points-to Analysis with Saturation;Proceedings of the ACM on Programming Languages;2024-06-20

3. Efficient Construction of Practical Python Call Graphs with Entity Knowledge Base;International Journal of Software Engineering and Knowledge Engineering;2024-05-22

4. Seneca: Taint-Based Call Graph Construction for Java Object Deserialization;Proceedings of the ACM on Programming Languages;2024-04-29

5. Data Lineage Analysis for Enterprise Applications by Manta: The Story of Java and C# Scanners;Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice;2024-04-14

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3