Abstract
Learning ontologies from software requirements specifications with individuals and relations between individuals to represent detailed information, such as input, condition and expected result of a requirement, is a difficult task. System specification ontologies (SSOs) can be developed from software requirement specifications to represent requirements and can be used to automate some time-consuming activities in software development processes. However, manually developing SSOs to represent requirements and domain knowledge of a software system is a time-consuming and a challenging task. The focus of this PhD is how to create ontologies semi-automatically from SRS. We will develop a framework that can be a possible solution to create semi-automatically ontologies from SRS. The developed framework will mainly be evaluated by using the constructed ontologies in the software testing process and automating a part of it. i.e. test case generation.
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Individuals and instances are same in our context. In OWL language, individuals are known as instances as well.
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Acknowledgments
I would like to thank and gratefully acknowledge my supervisors, Dr. Vladimir Tarasov, Dr. He Tan from School of Engineering, Jönköping university and Dr. Birgitta Lindström from Skövde university for their support, motivation, valuable comments and guidance. This work is part of OSTAG project, funded from KK-Foundation by grant KKS-20140170 and will be carried at School of Engineering, Jönköping University, Jönköping.
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Ismail, M. (2017). Ontology Learning from Software Requirements Specification (SRS). In: Ciancarini, P., et al. Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10180. Springer, Cham. https://doi.org/10.1007/978-3-319-58694-6_39
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DOI: https://doi.org/10.1007/978-3-319-58694-6_39
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