Evolutionary Generation of Test Data for Paths Coverage Based on Balance Optimization Theory

doi:10.3969/j.issn.0372-2112.2020.07.008

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Evolutionary Generation of Test Data for Paths Coverage Based on Balance Optimization Theory

更新时间：2025-07-08

- Evolutionary Generation of Test Data for Paths Coverage Based on Balance Optimization Theory
- Acta Electronica Sinica Vol. 48, Issue 7, Pages: 1303-1310(2020)
- 作者机构：
  
  1. 牡丹江师范学院计算机与信息技术学院,黑龙江,牡丹江,157011
  2. 牡丹江医学院卫生管理学院,黑龙江,牡丹江,157011
  3. 天津大学智能与计算学部,天津,300350
  4. 大连理工大学计算机科学与技术学院,辽宁,大连,116024
  5. 牡丹江师范学院计算机与信息技术学院,黑龙江,牡丹江,157011
  6. 牡丹江医学院卫生管理学院,黑龙江,牡丹江,157011
  7. 天津大学智能与计算学部,天津,300350
  8. 大连理工大学计算机科学与技术学院,辽宁,大连,116024
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2020.07.008
  CLC： TP311
- Published Online：25 July 2020，
  
  Published：2020
- 稿件说明：
移动端阅览
Evolutionary Generation of Test Data for Paths Coverage Based on Balance Optimization Theory[J]. Acta Electronica Sinica, 2020, 48(7): 1303-1310.
DOI：

Evolutionary Generation of Test Data for Paths Coverage Based on Balance Optimization Theory[J]. Acta Electronica Sinica, 2020, 48(7): 1303-1310. DOI： 10.3969/j.issn.0372-2112.2020.07.008.

摘要

为了快速生成覆盖目标路径的测试数据，提出在测试数据进化生成中，利用种群中个体穿越程序各分支的均衡程度调整进化过程.首先，在个体运行被测程序后，统计个体穿越各分支节点真假分支的情况；然后，设计并计算个体穿越程序的均衡度；最后，计算个体对程序均衡度的影响，使对程序均衡度影响大的个体具有较高的适应值，有更多机会参与到后续进化中，有效地提高了测试数据的生成效率.基准程序和工业用例的实验结果表明，与同类方法比较，所提出的方法在生成测试数据的运行时间与成功率方面具有优越性.

Abstract

In order to speed up the generation of test data that covers the target path

the paper makes good use of the balance of individual traversing program to adjust the evolutionary process of generating test data. First

after the individuals run the program

the number of individuals crossing the true and false branches of each branch node is counted. Then

the program balance is designed and calculated. Finally

the influence on the program balance of each individual is calculated. The individual with high influence has a bigger fitness value to have greater chance to participate in subsequent evolution. The proposed method effectively improves the efficiency of test data generation. The experiment results of benchmark programs and industrial cases show that our methods have superiority in running time and success rate of test data generation when compared with similar methods.

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Related Author

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GONG Dun-wei

ZHANG Yan

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ZHANG Yan

GONG Dun-wei

LIAO Wei-zhi

Related Institution

1. School of Information and Electrical Engineering, China University of Mining and Technology

Department of Computer Science and Technology, Mudanjiang Normal University

School of Information and Electrical Engineering, China University of Mining and Technology

School of Information and Electrical Engineering China University of Mining and Technology Xuzhou Jiangsu China

Department of Computer Science and Technology Mudanjiang Normal University Mudanjiang Heilongjiang China

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