URMG: Enhanced CBMG-Based Method for Automatically Testing Web Applications in the Cloud

作     者：Xiaolin Xu Hai Jin Song Wu Lixiang Tang Yihong Wang 

作者机构：Services Computing Technology and System Lab and Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2014年第19卷第1期

页      面：65-75页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(No.61232008) the National High-Tech Research and Development(863)Program of China(Nos.2013AA01A213 and 2013AA01A208) Chinese Universities Scientific Fund(No.2013TS094) Guangzhou Science and Technology Program(No.2012Y2-00040) 

主　　题：cloud web application performance evaluation customer behavior user representation 

摘      要：To satisfy the rapid growth of cloud technologies, a large number of web applications have been developed and deployed, and these applications are being run in clouds. Due to the scalability provided by clouds, a single web application may be concurrently visited by several millions or billions of users. Thus, the testing and performance evaluations of these applications are increasingly important. User model based evaluations can significantly reduce the manual work required, and can enable us to determine the performance of applications under real runtime environments. Hence, it has become one of the most popular evaluation methods in both industry and academia. Significant efforts have focused on building different kinds of models using mining web access logs, such as Markov models and Customer Behavior Model Graph （CBMG）. This paper proposes a new kind of model, named the User Representation Model Graph （URMG）, which is built based on CBMG. It uses an algorithm to refine CBMG and optimizes the evaluations execution process. Based on this model, an automatic testing and evaluation system for web applications is designed, implemented, and deployed in our test cloud, which is able to execute all of the analysis and testing operations using only web access logs. In our system, the error rate caused by random access to applications in the execution phase is also reduced, and the results show that the error rate of the evaluation that depends on URMG is 50% less than that which depends on CBMG.