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Titlebook: Knowledge-Based Software Engineering: 2018; Proceedings of the 1 Maria Virvou,Fumihiro Kumeno,Konstantinos Oikonomo Conference proceedings

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Analysis of Specification in Japanese Using Natural Language Processing,se to a state transition model is desired to help detect ambiguity and contradiction points of the specification. This paper proposes a method for this purpose, and reports on the result of applying the method to a specification example of an electric pot.
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Moral Education for Adults for Information Ethics to Effect the Unknown Problem,al education. The self-debate is thinking oneself, worrying this and that and putting together oneself. According to case studies, we could clarify that subjects were able to reflect upon themselves and acquire knowledge about information ethics through the self-debate. In this paper, we report the result of the education.
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Conference proceedings 2019k place on August 27–30, 2018 on the island of Corfu, Greece. The JCKBSE is a well-established international biennial conference that focuses on the applications of Artificial Intelligence in Software Engineering. The JCKBSE 2018 was organized by the Department of Informatics of the University of Pi
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Requirements Exploration by Comparing and Combining Models of Different Information Systems,models are combined so as to resolve the problems of stakeholder. To validate and discuss our method, we applied it to three sets of activities: room and seat booking, driving and taxi, and rainy report and wiper control. Three different notations are used for each case: use case diagrams, activity diagrams and data flow diagrams.
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Ripple Effect Analysis Method of Data Flow Diagrams in Modifying Data Flow Requirements,hod enables to specify areas of ripple effects of data flow diagrams in deletion and/or modification of requirements. Our method will be illustrated with examples using a prototype system based on the method.
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Deriving Successful Factors for Practical AI System Development Projects Using Assurance Case, project. To facilitate this, we propose a method of assessing an AI system development project by using an assurance case based on quality sub-characteristics of functionality to derive project success factors.
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