Validation test case generation based on safety analysis ontology

Fan, Chin-Feng; Wang, Wen-Shing

doi:10.1016/j.anucene.2012.02.001

Cited by 5 publications

(6 citation statements)

References 7 publications

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“…Other than being the prime use case of ontologies in the context of the Semantic Web, similar applications can be also found outside the strict context of on-line Web resources. An example is the Safety Analysis Ontology used in a system for systematically generating validation test cases from a safety analysis report annotated with terms from the ontology (Fan and Wang, 2012;Tseng and Fan, 2013). The system uses the machine-processable information in these annotations in order to generate tests that provenly cover all cases discussed in the (human-readable, textual) report.…”

Section: Ontology Applicationsmentioning

confidence: 99%

A conceptualization of a nuclear or radiological emergency

Konstantopoulos

Ikonomopoulos

2015

Nuclear Engineering and Design

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Section: Ontology Applicationsmentioning

confidence: 99%

A conceptualization of a nuclear or radiological emergency

Konstantopoulos

Ikonomopoulos

2015

Nuclear Engineering and Design

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“…The safety analysis report (SAR) document was a credible source for the automated validation of TCG for the nuclear industry systems [43]. Accidents and associated safety measures are crucial elements enclosed in the proposed approach.…”

Section: Rq2: What Are the State-of-the-art Techniques Of Ontology-based Regression Testing?mentioning

confidence: 99%

“…Validation of approaches. Although test case grouping presented in [39] helps remove the failed services, it still shows limitations in prioritizing test cases as low prioritized test cases might be grouped with the high prioritized test case [43]. Grouping high and low priority test cases is justified and plausible only if it is supported by previously evaluated criteria [22,42].…”

Section: Rq2: What Are the State-of-the-art Techniques Of Ontology-based Regression Testing?mentioning

confidence: 99%

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Ontology-Based Regression Testing: A Systematic Literature Review

et al. 2021

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Web systems evolve by adding new functionalities or modifying them to meet users’ requirements. Web systems require retesting to ensure that existing functionalities are according to users’ expectations. Retesting a web system is challenging due to high cost and time consumption. Existing ‘systematic literature review’ (SLR) studies do not comprehensively present the ontology-based regression testing approaches. Therefore, this study focuses on ontology-based regression testing approaches because ontologies have been a growing research solution in regression testing. Following this, a systematic search of studies was performed using the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines. A total of 24 peer-reviewed studies covering ontologies (semantic and inference rules) and regression testing, published between 2007 and 2019, were selected. The results showed that mainly ontology-based regression testing approaches were published in 2011–2012 and 2019 because ontology got momentum in research in other fields of study during these years. Furthermore, seven challenges to ontology-driven regression testing approaches are reported in the selected studies. Cost and validation are the main challenges examined in the research studies. The scalability of regression testing approaches has been identified as a common problem for ontology-based and other benchmark regression testing approaches. This SLR presents that the safety of critical systems is a possible future research direction to prevent human life risks.

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“…Systems based on ontologies are modeled into inputs in combinatorial testing and used to generate test cases. A case study was carried out in [18] that demonstrated the applications of ontology-based 'test case generation' (TCG) in an industrial setting. This study proposes an ontology-based technique that generates different scenarios to reveal faults in a system.…”

Section: Introductionmentioning

confidence: 99%

An Ontology Based Test Case Prioritization Approach in Regression Testing

Hasnain¹,

Jeong²,

Pasha³

et al. 2021

Computers, Materials &Amp; Continua

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Regression testing is a widely studied research area, with the aim of meeting the quality challenges of software systems. To achieve a software system of good quality, we face high consumption of resources during testing. To overcome this challenge, test case prioritization (TCP) as a sub-type of regression testing is continuously investigated to achieve the testing objectives. This study provides an insight into proposing the ontology-based TCP (OTCP) approach, aimed at reducing the consumption of resources for the quality improvement and maintenance of software systems. The proposed approach uses software metrics to examine the behavior of classes of software systems. It uses Binary Logistic Regression (BLR) and AdaBoostM1 classifiers to verify correct predictions of the faulty and non-faulty classes of software systems. Reference ontology is used to match the code metrics and class attributes. We investigated five Java programs for the evaluation of the proposed approach, which was used to achieve code metrics. This study has resulted in an average percentage of fault detected (APFD) value of 94.80%, which is higher when compared to other TCP approaches. In future works, large sized programs in different languages can be used to evaluate the scalability of the proposed OTCP approach.

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Validation test case generation based on safety analysis ontology

Cited by 5 publications

References 7 publications

A conceptualization of a nuclear or radiological emergency

A conceptualization of a nuclear or radiological emergency

Ontology-Based Regression Testing: A Systematic Literature Review

An Ontology Based Test Case Prioritization Approach in Regression Testing

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