Automated Test Generation Based on Colored Petri Net and Improved Depth First Search for Train Control System
Jianfeng Cheng, Xiaoyu Zhao, Jiquan Liu, Yu Zhang · 2019
Testing of the train control system is a vital factor to ensure the functional and reliability of railway signal system. In the paper, an automated test generation approach based on colored petri net (CPN) and the improved depth first search algorithm, which takes the full path coverage and the full node coverage as criterions, is presented for the train control system. Firstly, CPN model is designed by the functional requirements specification of the Chinese Train Control System Level 3 (CTCS -3) train control system and modeling rules. Secondly, test case suite with least number of repeated paths and least number of test cases is automatically generated by the proposed approach. Finally, the case study of on-board subsystem is employed, which is to show that the proposed approach can deal with complex endless (self-)loops and improve test efficiency.