云计算环境下嵌入式虚拟仪器软件自动测试技术
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摘要
采用传统技术对嵌入式虚拟仪器软件进行研究,缺少对集成部分的测试,导致测试精准度较低,为了解决该问题,提出了云计算环境下嵌入式虚拟仪器软件自动测试技术。在云计算环境下,按照测试方案设计测试实施步骤,选择具有代表性的样本进行学习,获取样本消息和原始窗口序列。针对单元模块进行测试,按照设计方案,将完成设计的模块连接起来,形成集成模块,按照用户提出的需求进行产品认定,吸取用户提出的意见,对测试结果进行验收,由此完成对测试步骤的分析。通过学习结果对可测试软件因子进行配置,修改样本消息序列值来获取大量衍生消息,进而实现对软件的自动测试。由对比结果可知,该技术具有90%的测试精准度。
In view of the research on embedded virtual instrument software,the traditional technology is short of testing the integrated part,which leads to the low precision of the test.In order to solve this problem,an automatic test technology of embedded virtual instrument software under the cloud computing environment is put forward.In the cloud computing environment,the test implementation steps are designed according to the test scheme,the representative sample is selected to learn,and the sample message and the original window sequence are obtained.According to the design scheme,the module is tested and connected to form an integrated module.According to the requirements proposed by the users,the product is identified.The user's opinion is drawn,the test results are verified,and the analysis to the test steps is completed.The test software factors are configured through the learning results,and the sample message sequence values are modified to obtain a large number of derived messages,and then the automatic testing of the software is realized.The result from comparision shows that this technology has 90% accuracy,and lays the foundation for software product research and development.
In view of the research on embedded virtual instrument software,the traditional technology is short of testing the integrated part,which leads to the low precision of the test.In order to solve this problem,an automatic test technology of embedded virtual instrument software under the cloud computing environment is put forward.In the cloud computing environment,the test implementation steps are designed according to the test scheme,the representative sample is selected to learn,and the sample message and the original window sequence are obtained.According to the design scheme,the module is tested and connected to form an integrated module.According to the requirements proposed by the users,the product is identified.The user's opinion is drawn,the test results are verified,and the analysis to the test steps is completed.The test software factors are configured through the learning results,and the sample message sequence values are modified to obtain a large number of derived messages,and then the automatic testing of the software is realized.The result from comparision shows that this technology has 90% accuracy,and lays the foundation for software product research and development.
引文
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[13]兰娅勋,李振坤.MonkeyRunner环境用例脚本化的Android软件测试模型[J].科技通报,2017,33(9):96-99.
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[15]郭德贵,王冠成,吕帅,等.peC语言的部分求值器及在编译器测试中的应用[J].软件学报,2017,28(5):1221-1232.
[2]游桂贞,刘布麒,周权强.自动化测试技术在网络控制软件测试中的应用[J].机车电传动,2017,22(5):79-82.
[3]朱龙.船摇隔离度自动化软件的设计与测试[J].舰船科学技术,2017,21(7x):161-163.
[4]陈晔.关于软件设计可靠性自动化测试仿真研究[J].计算机仿真,2017,34(6):281-284.
[5]田鸿运,刘青凯,成杰,等.一种面向高性能数值模拟软件的自动化测试平台[J].计算机工程与科学,2017,39(11):1980-1985.
[6]王砺磊,曾霞,林望,等.ATCase:一个基于多项式约束求解的数值程序测试用例自动生成工具[J].系统科学与数学,2017,37(7):1704-1721.
[7]李筱,周严,李孟宸,等.C/C++程序静态内存泄漏警报自动确认方法[J].软件学报,2017,28(4):827-844.
[8]李春光,周晓红,董龙明.符号执行火控系统诸元解算程序测试用例生成技术[J].火力与指挥控制,2017,42(7):157-160.
[9]朱晓珺,韩林,邹香玲.基于SIFT特征与多层BP神经网络的钢板缺陷检测算法[J].组合机床与自动化加工技术,2017,18(10):54-56.
[10]刘鹏,吕广宪,康先果,等.基于IEC 61968的配电网信息交互一致性测试技术应用[J].电力系统自动化,2017,41(6):142-146.
[11]张斌,刘文怡,魏月娟,等.一种基于超声阻抗和回波能量的液位检测方法[J].传感技术学报,2017,30(11):1625-1629.
[12]郭文生,汪勇,杨霞,等.Codecomb:基于符号执行的嵌入式软件测试案例自动生成与缺陷检测[J].小型微型计算机系统,2017,38(6):1250-1255.
[13]兰娅勋,李振坤.MonkeyRunner环境用例脚本化的Android软件测试模型[J].科技通报,2017,33(9):96-99.
[14]刘阳,谭坚文,曾德平,等.基于虚拟仪器技术的聚焦超声换能器电声转换效率自动测试系统[J].中国生物医学工程学报,2017,36(3):322-328.
[15]郭德贵,王冠成,吕帅,等.peC语言的部分求值器及在编译器测试中的应用[J].软件学报,2017,28(5):1221-1232.
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