基于大数据分析的嵌入式软件测试系统设计

Design of Embedded Software Testing System Based on Big Data Analysis

为进一步提升我国的嵌入式软件测试水平,提出一种基于大数据分析的嵌入式软件测试系统。该系统基于静态负载均衡算法进行了分布式软件测试系统的设计,同时基于需求优先级对静态负载均衡算法进行了优化。实验结果表明,改进后的静态负载均衡算法过程的测试用例利用率提升明显;与改进前的测试系统相比,基于改进静态负载均衡的嵌入式软件分布式测试系统的测试正确率得到了明显提升,达到了99.5%。以上实验结果验证了本研究对于测试系统的设计和改进一定程度上提升了其测试性能,具有一定的现实参考价值。

In order to further improve the level of embedded software testing in China, an embedded software testing system based on big data analysis is proposed. A distributed software testing system is designed based on static load balancing algorithm, and the static load balancing algorithm is optimized based on demand priority. The experimental results show that the test case utilization of the improved static load balancing algorithm process is significantly improved;Compared with the test system before improvement, the test accuracy of the embedded software distributed test system based on improved static load balancing has been significantly improved, reaching 99.5%. The above experimental results verify that this research has a certain practical reference value for the design and improvement of the test system to improve its test performance to a certain extent.