摘要
在当前FAO系统大规模建设背景下,作为典型的安全苛求系统,FAO系统运营服务水平和安全可靠性的需求日益增高,实际应用之前需要对其进行全面严格的测试,而现有的测试用例生成方法一般难以满足对安全性测试的需求。因此,提出一种安全测试用例自动生成方法:以全自动运行系统中的障碍物脱轨检测场景为例,首先根据场景安全约束建立带安全约束的时间自动机模型,定义CF-SC安全测试覆盖准则,用于刻画场景运行下危险致因和安全约束的测试需求;然后针对此覆盖准则,设计一种考虑安全约束的深度优先搜索算法,算法在深度优先搜索框架下增加补充判别策略,用于覆盖安全测试需求的边和节点,实现安全测试用例的自动化生成。结果表明,CF-SC安全测试覆盖准则强于传统的路径覆盖准则,相对于现有方法,本方法在实现路径全覆盖的基础上,可对潜在的危险致因进行充分测试,对含有安全约束的路径覆盖率提升达33%,可有效满足安全测试需求,对提高全自动运行系统安全性具有重要研究意义和应用价值。
In the context of large-scale construction of fully automatic operation(FAO)systems,there is an increasing demands for the operational service level and safety reliability of such systems,which are regarded as typical safety-critical systems.Comprehensive and rigorous testing is required before practical application.However,existing test case generation methods often fail to meet the requirements for safety testing.To address this,an automatic safety test case generation method was proposed.Using the obstacle and derailment detection scenarios in a FAO system as examples,a timed automaton model incorporating safety constraints was first established based on the safety constraints of the scenarios.A CF-SC safety test coverage criterion was defined to represent the testing requirements for causes of hazards and safety constraints under scenario operation.Then,for this coverage criterion,a depth-first search algorithm considering safety constraints was designed.The algorithm enhanced the depth-first search framework with supplementary decisionmaking strategies to cover edges and nodes of safety testing requirements,achieving automatic generation of safety test cases.The results showed that the CF-SC criterion was stronger than traditional path coverage criteria.Compared to existing methods,the proposed method ensured full path coverage while enabling thorough testing of potential hazard causes.Path coverage with safety constraints was improved by 33%,effectively meeting the requirements for safety testing.This has important research significance and application value for the enhancement of FAO system safety.
作者
冉怡明
张亚东
饶畅
江磊
RAN Yiming;ZHANG Yadong;RAO Chang;JIANG Lei(School of Information Science and Technology,Southwest Jiaotong University,Chengdu 611756,China;Sichuan Train Operation Control Technology Engineering Research Center,Chengdu 611756,China;College of Traffic and Transportation,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《铁道标准设计》
北大核心
2025年第6期178-186,共9页
Railway Standard Design
基金
四川省自然科学基金项目(2022NSFSC1878)
中央高校基本科研业务费专项资金资助项目(2682022ZTPY084)
重庆市教委科技计划(KJQN202300750)。
