中国科学院软件研究所机构知识库
Advanced  
ISCAS OpenIR  > 计算机科学国家重点实验室  > 期刊论文
Title:
基于约束的软件失效域识别与特征分析
Alternative Title: a constraint-based approach to identifying and analyzing failure-causing regions
Author: 孙昌爱
Keyword: Quality control ; Testing
Source: 软件学报
Issued Date: 2012
Volume: 23, Issue:7, Pages:1688-1701
Department: 北京科技大学计算机与通信工程学院;中国科学院软件研究所计算机科学国家重点实验室;
Abstract: 随机测试是实践中广泛采用的一种黑盒测试方法.近年来提出的适应性随机测试方法改进了随机测试的不足,仿真实验结果表明,改进效果取决于软件失效域的特征.提出以测试约束刻画软件失效域在输入域上的分布,探讨了基于现有的程序分析技术构造测试约束的过程,讨论了基于测试约束的软件失效域的特征分析方法.以一个实例软件验证所提出的测试约束构造过程及其软件失效域特征分析方法.测试约束揭示了软件故障的触发与传播的内在机制,基于测试约束的软件失效域的特征分析方法有助于改进测试用例的设计质量以及评价适应性随机测试方法的适用性.
English Abstract: Random testing is a widely practiced black-box testing technique. Recently, adaptive random testing has been proposed to improve the random testing, and simulation results show that the improvements depend on the characteristic of failure-causing regions of program under test. This paper presents the concept of test constraints and employs them to specify the distribution of failure-causing regions within the input domain of program under test. Characteristic analysis of failure-causing regions can be conducted on the base of their test constraints, which are derived using the available program analysis techniques. To evaluate the proposed technique, a case study on a real-life application was conducted, and the results show that the proposed test constraint provides an insight into how a failure is triggered and propagated, and the constraint-based analysis helps to improve the quality of test case design and assess the applicability of the adaptive random testing. © 2012 ISCAS.
Language: 中文
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/14655
Appears in Collections:计算机科学国家重点实验室 _期刊论文

Files in This Item:
File Name/ File Size Content Type Version Access License
基于约束的软件失效域识别与特征分析.pdf(1516KB)----限制开放 联系获取全文

Recommended Citation:
孙昌爱. 基于约束的软件失效域识别与特征分析[J]. 软件学报,2012-01-01,23(7):1688-1701.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[孙昌爱]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[孙昌爱]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2020  中国科学院软件研究所 - Feedback
Powered by CSpace