[1]高峰青 王晓军.基于分支插桩的改进型评价模型及其应用[J].计算机技术与发展,2012,(10):98-100.
 GAO Feng-qing,WANG Xiao-jun.A Promoted Mode Based on Branch-stubbing & Applications[J].,2012,(10):98-100.
点击复制

基于分支插桩的改进型评价模型及其应用()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年10期
页码:
98-100
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
A Promoted Mode Based on Branch-stubbing & Applications
文章编号:
1673-629X(2012)10-0098-03
作者:
高峰青 王晓军
南京邮电大学计算机学院
Author(s):
GAO Feng-qing WANG Xiao-jun
School of Computer, Nanjing University of Posts & Telecommunications
关键词:
遗传算法分支插桩节点覆盖适应度函数测试用例
Keywords:
genetic algorithm branch-stubbing node-covering fitness function test case
分类号:
TP31
文献标志码:
A
摘要:
软件测试是软件开发过程中极其重要的一环,提高软件测试的自动化程度对于确保软件开发质量、降低软件开发成本非常重要,而提高生成测试用例的自动化程度又是提高测试自动化程度的关键。当今用遗传算法生成测试数据是一种行之有效的方法。Korel所提出的“分支函数”插装法在一定程度上优化了算法的执行效率。文中在此基础上。结合节点覆盖的思想,设计出一个能更好指导算法执行过程的模型。实验证明该适应度模型比单纯的插桩方式的遗传算法生成测试用例更加高效
Abstract:
Software test is an important step during software development. Improving the automation of software testing can increase the robustness of software and decrease the cost of development. The key of improving the automation ability of testing is improving the automatic test data generation. Now the genetic algorithm (GA) is a efficient way for producing test cases. Branch-stubbing proposed by Korel,is aldant for GA to a certain extent. Considering the node-covering,show a promoted mode. From the experimentation,see that it takes a good effect,and is prior to branch-stubbing method

相似文献/References:

[1]冯智明,苏一丹,覃华,等.基于遗传算法的聚类与协同过滤组合推荐算法[J].计算机技术与发展,2014,24(01):35.
 FENG Zhi-ming,SU Yi-dan,QIN Hua,et al.Recommendation Algorithm of Combining Clustering with Collaborative Filtering Based on Genetic Algorithm[J].,2014,24(10):35.
[2]余晓光 严洪森 殷乾坤.基于Flexsim的车间调度优化[J].计算机技术与发展,2010,(03):44.
 YU Xiao-guang,YAN Hong-sen,YIN Qian-kun.Workshops Scheduling Optimization Based on Flexsim Simulation[J].,2010,(10):44.
[3]贺计文 宋承祥 刘弘.基于遗传算法的八数码问题的设计及实现[J].计算机技术与发展,2010,(03):105.
 HE Ji-wen,SONG Cheng-xiang,LIU Hong.Design and Implementation of Eight Puzzle Problem Based on Genetic Algorithms[J].,2010,(10):105.
[4]沈珏萍 庄亚明.基于Agent的二级供应链企业自动谈判研究[J].计算机技术与发展,2010,(03):121.
 SHEN Jue-ping,ZHUANG Ya-ming.A Research for Company Automatic Negotiation in Secondary Supply Chain Based on Agent[J].,2010,(10):121.
[5]张磊 王晓军.基于遗传算法的业务流程测试[J].计算机技术与发展,2010,(03):155.
 ZHANG Lei,WANG Xiao-jun.Test of Business Process Based on Genetic Algorithm[J].,2010,(10):155.
[6]曹道友 程家兴.基于改进的选择算子和交叉算子的遗传算法[J].计算机技术与发展,2010,(02):44.
 CAO Dao-you,CHENG Jia-xing.A Genetic Algorithm Based on Modified Selection Operator and Crossover Operator[J].,2010,(10):44.
[7]范维博 周俊 许正良.应用遗传算法求解第一类装配线平衡问题[J].计算机技术与发展,2010,(02):194.
 FAN Wei-bo,ZHOU Jun,XU Zheng-liang.Appication of Genetic Algorithm to Assembly Line Balancing[J].,2010,(10):194.
[8]熊伟平 曾碧卿.几种仿生优化算法的比较研究[J].计算机技术与发展,2010,(03):9.
 XIONG Wei-ping,ZENG Bi-qing.Studies on Some Bionic Optimization Algorithms[J].,2010,(10):9.
[9]余晓光 严洪森.基于禁忌搜索遗传混合算法的装配线平衡[J].计算机技术与发展,2010,(05):5.
 YU Xiao-guang,YAN Hong-sen.Assembly Line Balancing Based on Tabu Search and Genetic Hybrid Algorithm[J].,2010,(10):5.
[10]黄永聪 张旭[] 吴义纯 吴琦 程家兴.改进的径向基函数网络的研究及应用[J].计算机技术与发展,2010,(05):158.
 HUANG Yong-cong,ZHANG Xu,WU Yi-chun,et al.Research and Application of Improved Genetic Algorithm-Based RBFANN[J].,2010,(10):158.

备注/Memo

备注/Memo:
国家科技支撑计划项目(2007BAH17B04)高峰青(1986-),男,硕士研究生,主要研究方向为分布计算技术与应用;王晓军,副教授,硕士研究生导师,主要研究领域为分布计算技术与应用
更新日期/Last Update: 1900-01-01