DART

Author:

Godefroid Patrice1,Klarlund Nils1,Sen Koushik2

Affiliation:

1. Bell Laboratories, Lucent Technologies

2. University of Illinois at Urbana-Champaign, Urbana, IL

Abstract

We present a new tool, named DART, for automatically testing software that combines three main techniques: (1) automated extraction of the interface of a program with its external environment using static source-code parsing; (2) automatic generation of a test driver for this interface that performs random testing to simulate the most general environment the program can operate in; and (3) dynamic analysis of how the program behaves under random testing and automatic generation of new test inputs to direct systematically the execution along alternative program paths. Together, these three techniques constitute Directed Automated Random Testing , or DART for short. The main strength of DART is thus that testing can be performed completely automatically on any program that compiles -- there is no need to write any test driver or harness code. During testing, DART detects standard errors such as program crashes, assertion violations, and non-termination. Preliminary experiments to unit test several examples of C programs are very encouraging.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 897 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. Knowledge transfer based many-objective approach for finding bugs in multi-path loops;Complex & Intelligent Systems;2024-01-24

2. VISGRADER: Automatic Grading of D3 Visualizations;IEEE Transactions on Visualization and Computer Graphics;2024-01

3. Impacts of Program Structures on Code Coverage of Generated Test Suites;Product-Focused Software Process Improvement;2023-12-02

4. Neural-Based Test Oracle Generation: A Large-Scale Evaluation and Lessons Learned;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

5. LExecutor: Learning-Guided Execution;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30

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