本文選題：軟件測(cè)試　切入點(diǎn)：測(cè)試用例集縮減　出處：《西北工業(yè)大學(xué)學(xué)報(bào)》2017年03期

【摘要】：軟件測(cè)試是在軟件開(kāi)發(fā)過(guò)程中,用以確認(rèn)和驗(yàn)證軟件質(zhì)量的主要方法。然而測(cè)試用例冗余是軟件測(cè)試面臨的一個(gè)重要難題。在回歸測(cè)試中,人們會(huì)根據(jù)新的測(cè)試需求不斷補(bǔ)充大量的測(cè)試用例,這也會(huì)造成測(cè)試用例冗余的出現(xiàn)。雖然現(xiàn)在已有很多工具通過(guò)重用測(cè)試用例集來(lái)降低回歸測(cè)試的成本,但回歸測(cè)試依然可能是極其耗時(shí)的過(guò)程。為此,人們提出了各種方法,對(duì)已生成的測(cè)試用例集進(jìn)行縮減。雖然一些現(xiàn)有的數(shù)據(jù)縮減方法可以減少冗余數(shù)據(jù),但往往會(huì)削弱排除錯(cuò)誤的能力。文章通過(guò)引入變異分析和覆蓋準(zhǔn)則來(lái)建立回歸測(cè)試用例集縮減實(shí)驗(yàn)的數(shù)學(xué)模型,并采用多目標(biāo)進(jìn)化優(yōu)化方法來(lái)進(jìn)行求解優(yōu)化模型。最后采用Siemens suit基準(zhǔn)數(shù)據(jù)集及工業(yè)space大程序進(jìn)行驗(yàn)證,并使用3種進(jìn)化優(yōu)化算法進(jìn)行測(cè)試用例集縮減。事實(shí)上,對(duì)于SIR小程序,NSGA-Ⅱ算法表現(xiàn)最優(yōu);對(duì)于space大程序,則是MOEA/D-PBI優(yōu)于NSGA-Ⅱ。實(shí)驗(yàn)結(jié)果表明,在保證缺陷檢測(cè)能力不下降的同時(shí),該方法可以有效地縮減測(cè)試用例集。
[Abstract]:Software testing is the main method to confirm and verify the quality of software in the process of software development. However, redundancy of test cases is an important problem in software testing. People continue to add a large number of test cases to new test requirements, which can also lead to redundancy in test cases, although there are many tools that reduce the cost of regression testing by reusing test case sets. But regression testing can still be an extremely time-consuming process. For this reason, a variety of methods have been proposed to reduce the set of test cases that have been generated, although some existing data reduction methods can reduce redundant data. However, it often weakens the ability to eliminate errors. In this paper, the mathematical model of regression test set reduction experiment is established by introducing variation analysis and coverage criterion. Finally, the optimization model is solved by using multi-objective evolutionary optimization method. Finally, Siemens suit datum data set and industrial space program are used to verify, and three evolutionary optimization algorithms are used to reduce test case set. In fact, For SIR Mini Programs, NSGA- 鈪，

本文編號(hào)：1654476