Domain Ontology Construction and Evaluation for the Entire Process of Software Testing

Sun, Zhe; Hu, Chi; Li, Chunlei; Wu, Linbo

doi:10.1109/access.2020.3037188

Cited by 16 publications

(9 citation statements)

References 24 publications

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“…Using the deep learning technique, new inference rules were found based on many semantic networks which are formed by ontology triples and relations [11]. During the software testing phase, ontology solves the knowledge silo problem which contains the software testing process information and failure details [12]. The cross-domain knowledge is integrated into multi-aspect ontology which supports the decision system [13].…”

Section: Literature Reviewmentioning

confidence: 99%

Augmentation of contextual knowledge based on domain dominant words for IoT applications interoperability

Shanmurthy

Poongodi

Balusamy

et al. 2022

IJEECS

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Semantic web technology is adapted to the internet of things (IoT) for web - based applications to globally connect the services. Web ontology language (OWL) domain ontology is a powerful machine - readable language for domain knowledge representation. The developer stored the IoT application relevant ontology in a repository or catalogue. Hence, IoT application - related ontology files are available for reus e, but many of the IoT application - relevant ontology files are publicly not available or inaccessible. The proposed idea is to extract the contextual knowledge of IoT applications that contain inaccessible ontology files. The context - wise specific domain I oT applications are not obtainable, hence respective ontology - based research papers are identified and their frequent terms are computed. The selected contextual dominant frequent terms from the transport domain are passed into the skip - gram flavour of wor d2vector modelled n atural language processing ( NLP ) corpus which produces most similar terms. The domain experts select the appropriate terms to annotate in OWL ontology for contextual knowledge augmentation. Finally, 1422 contextual terms were generated b ased on dominant terms of selected IoT applications.

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Section: Literature Reviewmentioning

confidence: 99%

Augmentation of contextual knowledge based on domain dominant words for IoT applications interoperability

Shanmurthy

Poongodi

Balusamy

et al. 2022

IJEECS

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“…The second one is data enrichment by integrating ontologies to create semantic data and then make it understandable for different IIoT applications. We used EPOST (Entire Process Ontology on Software Testing) [28] to create and manipulate our ontology.…”

Section: Preprocessingmentioning

confidence: 99%

Reinforcement learning multi-agent system for faults diagnosis of mircoservices in industrial settings

Belhadi

Djenouri

Srivastava

et al. 2021

Computer Communications

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“…Com base em um estudo de caso, Sun et al (2020) elabora a ontologia de um processo completo de teste de software, abrangendo objetos, métodos e casos de teste. Com base nos resultados apresentados, esta ontologia tem por objetivo contribuir no compartilhamento e disseminação do conhecimento de domínio, além da melhoria do processo e qualidade do teste de software.…”

Section: Trabalhos Relacionadosunclassified

Uma Visão Ontológica Sobre os Testes de Software Utilizando Ontologia de Fundamentação-A (UFO-A)

Santos

Ribeiro²,

Schmitz

et al. 2021

Anais Da VII Escola Regional De Sistemas De Informação Do Rio De Janeiro (ERSI-RJ 2021)

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Este artigo apresenta um fragmento de modelo ontológico do domínio de testes de software, representado pelos principais objetos, papéis, relações, fases e artefatos produzidos. Posteriormente, são apresentadas duas abordagens conceituais complementares dos elementos envolvidos no teste de software, utilizando como base a Ontologia de Fundamentação-A (UFO-A), com o objetivo de fornecer uma compreensão mais clara da modelagem conceitual existente no processo de testes.

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Domain Ontology Construction and Evaluation for the Entire Process of Software Testing

Cited by 16 publications

References 24 publications

Augmentation of contextual knowledge based on domain dominant words for IoT applications interoperability

Augmentation of contextual knowledge based on domain dominant words for IoT applications interoperability

Reinforcement learning multi-agent system for faults diagnosis of mircoservices in industrial settings

Uma Visão Ontológica Sobre os Testes de Software Utilizando Ontologia de Fundamentação-A (UFO-A)

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