{"title":"A Method of Automatic Test Case Generation Based on CT-LSSVM Algorithm in FAO Systems","authors":"Sha Wang, Qingyuan Shang, Zhujun Ling, Dandan Liu, Xiangxian Chen","doi":"10.1109/ICITE50838.2020.9231435","DOIUrl":null,"url":null,"abstract":"The FAO system is a new-generation railway signaling system, the comprehensive and accurate testing is the main means to verify the safety and stability of the system, and the design and generation of test cases is an important link of the system testing. Traditionally, test cases are manually generated, which is inefficient, time-consuming and inaccurate. To solve this problem, we proposed an automatic test case generation method for the FAO system specified scenario using the CT-LSSVM algorithm. The CT algorithm was used to realize multi-factor combination to generate test cases, and the LSSVM method was used to predict and analyze the expected results of the test cases. The results showed that when the LSSVM method was used to model and analyze the test cases generated by the CT five-factor combination, the recognition rate of the calibration set was 96.58% and the recognition rate of the test set was 97.73%; At the same time, some test cases of the twelve-factor combination were predicted and analyzed, and the recognition rate reached 98.57%. This proves that the CT-LSSVM method can be applied to the test case generation of the FAO system.","PeriodicalId":112371,"journal":{"name":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","volume":"315 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 5th International Conference on Intelligent Transportation Engineering (ICITE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITE50838.2020.9231435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The FAO system is a new-generation railway signaling system, the comprehensive and accurate testing is the main means to verify the safety and stability of the system, and the design and generation of test cases is an important link of the system testing. Traditionally, test cases are manually generated, which is inefficient, time-consuming and inaccurate. To solve this problem, we proposed an automatic test case generation method for the FAO system specified scenario using the CT-LSSVM algorithm. The CT algorithm was used to realize multi-factor combination to generate test cases, and the LSSVM method was used to predict and analyze the expected results of the test cases. The results showed that when the LSSVM method was used to model and analyze the test cases generated by the CT five-factor combination, the recognition rate of the calibration set was 96.58% and the recognition rate of the test set was 97.73%; At the same time, some test cases of the twelve-factor combination were predicted and analyzed, and the recognition rate reached 98.57%. This proves that the CT-LSSVM method can be applied to the test case generation of the FAO system.