Evaluation System for Software Testing Tools in Complex Data Environment
Chao-Hsien Hsieh, Zhen Wang, Qing Zhang, Yubo Song, Xiaoyu Wu, Ziyi Wang, Shilong Wang, Jiahe Qi
- 发表年份
- 2021
- 引用次数
- 2
摘要
With the popularization of the Internet in recent years, the software industry is booming. In order to develop software products to meet the needs of users, software testing must be carried out. However, due to the complexity of the test environment, software testing faces great challenges. Therefore, an efficient system of test and evaluation is necessary. Unfortunately, there is no single tool that can fully test complex data at present. It is of great importance to select test tools for the reason that different test tools have different effects on the efficiency of integration testing. Therefore, this paper constructs a test and evaluation system based on different data environments. It helps testers to choose suitable test tools which include three commonly test software, Postman, JMeter, and Robot Framework. The performance of those test tools through the evaluation methods of standard deviation and incidence matrix. The experimental results show that the comprehensive performance of Postman is the better than JMeter and Robot Framework.
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