| 一种似然蜕变关系动态发现工具设计 |
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| 引用本文： | 范超,阳小华,闫仕宇,吴取劲,李萌.一种似然蜕变关系动态发现工具设计[J].南华大学学报(自然科学版),2018,32(2):81-86. |
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| 作者姓名： | 范超 阳小华 闫仕宇 吴取劲 李萌 |
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| 作者单位： | 南华大学计算机学院;中核集团高可信计算重点学科实验室 |
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| 基金项目： | 湖南省教育厅科学研究项目(16C1379)；衡阳市科技计划项目(2017KJ273) |
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| 摘 要： | 蜕变测试技术认为,测试中成功的测试用例可为构造蜕变关系提供有价值的信息,而似然蜕变关系的动态发现方法是根据已经成功运行的测试数据来发现蜕变关系的启发信息,基于一种似然蜕变关系发现算法的基本框架,进一步具体设计和实现算法,且开发相应的工具,实验表明该算法的可行性及工具的实用性.
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| 关 键 词： | 蜕变测试 蜕变关系 似然蜕变关系 算法实现 |
| 收稿时间： | 2018/1/24 0:00:00 |
Design of a Dynamic Discovery Tool for Likely Metamorphic Relation |
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| FAN Chao,YANG Xiao-hu,YAN Shi-yu,WU Qu-jing and LI Meng.Design of a Dynamic Discovery Tool for Likely Metamorphic Relation[J].Journal of Nanhua University:Science and Technology,2018,32(2):81-86. |
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| Authors: | FAN Chao YANG Xiao-hu YAN Shi-yu WU Qu-jing and LI Meng |
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| Institution: | 1.School of Computer,University of South China,Hengyang,Hunan 421001,China;2.CNNC Key Laboratory on High Trusted Computing,Hengyang,Hunan 421001,China,1.School of Computer,University of South China,Hengyang,Hunan 421001,China;2.CNNC Key Laboratory on High Trusted Computing,Hengyang,Hunan 421001,China,1.School of Computer,University of South China,Hengyang,Hunan 421001,China;2.CNNC Key Laboratory on High Trusted Computing,Hengyang,Hunan 421001,China,1.School of Computer,University of South China,Hengyang,Hunan 421001,China;2.CNNC Key Laboratory on High Trusted Computing,Hengyang,Hunan 421001,China and 1.School of Computer,University of South China,Hengyang,Hunan 421001,China;2.CNNC Key Laboratory on High Trusted Computing,Hengyang,Hunan 421001,China |
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| Abstract: | The technology of metamorphic testing considers that the successful test cases can provide valuable information for constructing the metamorphic relation,and the likely metamorphic relations dynamic discovery method can discover the heuristic information of the metamorphic relation based on the test data that has been successfully operated.Based on a dynamic likely metamorphic relations discovery algorithm,this paper designs and implements the corresponding tools,and verifies the feasibility of the algorithm through an example. |
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