首页 | 本学科首页   官方微博 | 高级检索  
     


Systematic scenario test case generation for nuclear safety systems
Affiliation:1. Computer Science Department University of Biskra, Algeria;2. LIRMM, CNRS and Montpellier University, France;3. LESIA Laboratory University of Biskra, Algeria
Abstract:ContextThe current validation tests for nuclear software are routinely performed by random testing, which leads to uncertain test coverage. Moreover, validation tests should directly verify the system’s compliance with the original user’s needs. Unlike current model-based testing methods, which are generally based on requirements or design models, the proposed model is derived from the original user’s needs in text through domain-specific ontology, and then used to generate validation tests systematically.ObjectiveOur first goal is to develop an objective, repeatable, and efficient systematic validation test scheme that is effective for large systems, with analyzable test coverage. Our second goal is to provide a new model-based validation testing method that reflects the user’s original safety needs.MethodA model-based scenario test case generation for nuclear digital safety systems was designed. This was achieved by converting the scenarios described in natural language in a Safety Analysis Report (SAR) prepared by the power company for licensing review, to Unified Modeling Language (UML) sequence diagrams based on a proposed ontology of a related regulatory standard. Next, we extracted the initial environmental parameters and the described operational sequences. We then performed variations on these data to systematically generate a sufficient number of scenario test cases.ResultsTest coverage criteria, which are the equivalence partition coverage of initial environment, the condition coverage, the action coverage and the scenario coverage, were met using our method.ConclusionThe proposed model-based scenario testing can provide improved testing coverage than random testing. A test suite based on user needs can be provided.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号