基于深度神经网络的GUI测试异构场景图像相似度分析  

Analysis of image similarity in heterogeneous scenarios of GUI testing based on deep neural networks

作　　者：蒋林呈 姜磊 陈纪龙 JIANG Lincheng;JIANG Lei;CHEN Jilong(Sichuan University,Chengdu 610065,China;National Key Laboratory of Fundamental Algorithms and Models for Engineering Simulation,Chengdu 610207,China)

机构地区：[1]四川大学,成都610065 [2]工程数值模拟基础算法与模型全国重点实验室,成都610207

出　　处：《计算机应用文摘》2024年第22期63-65,共3页

基　　金：国家重大专项(GJXM92579)。

摘　　要：在软件测试中,判断GUI异构场景的图像相似度是提高测试效率和质量的关键。文章提出了一种基于深度神经网络的图像相似度分析方法。其中,首先对GUI图像进行了预处理并通过VGG-16提取了图像特征,同时引入了OCR模块获取文本信息;在相似度计算阶段,分别计算了图像特征和文本的相似度,通过交叉熵损失函数和字符串匹配算法得到了相似度分数,最终进行了加权求和。经验证,该方法能有效抵抗设备差异导致的噪声和变形干扰,提高了GUI测试的效率和质量,为测试人员提供了准确、全面的结果和决策依据。In software testing,determining the image similarity of GUI heterogeneous scenes is the key to improving testing efficiency and quality.The article proposes an image similarity analysis method based on deep neural networks.Firstly,the GUI image was preprocessed and image features were extracted using VGG 16,while an OCR module was introduced to obtain text information.In the similarity calculation stage,the similarity between image features and text was calculated separately.The similarity scores were obtained through cross entropy loss function and string matching algorithm,and finally weighted sum was performed.After verification,this method can effectively resist noise and deformation interference caused by device differences,improve the efficiency and quality of GUI testing,and provide accurate and comprehensive results and decision making basis for testers.

关 键 词：软件测试 OCR 图像相似度 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]