@article{oai:miyazaki-u.repo.nii.ac.jp:00006345,
 author = {執行, 泰弘 and Katayama, Tetsuro and 片山, 徹郎 and Shigyo, Yasuhiro and Katayama, Tetsuro and 片山, 徹郎},
 journal = {宮崎大学工学部紀要, Memoirs of Faculty of Engineering, University of Miyazaki},
 month = {Sep},
 note = {Specifications are generally written in natural language. Natural language contains ambiguity. As a method of writing a specification without ambiguity, VDM which is a formal method exists. Because it is difficult to write specification languages such as VDM++ because they have strict grammars data types and system invariants that are not found in natural language specifications. This study attempts to generate automatically a VDM++ specification from the natural language specification by using machine learning. For automatic generation of VDM++, it is necessary to extract predicates corresponding to the function names and nouns corresponding to variable names from the natural language specification. However,it is difficult to generate a VDM++ specification by using only the extracted nouns and predicates. This paper proposes an approach to generate automatically a VDM++ specification from extracted words list. An identifier is generated from the extracted words, and the VDM++ specification can be generated by converting this identifier into a VDM++ grammar.},
 pages = {245--250},
 title = {機械学習を用いて自然言語仕様書から生成した分類リストを用いたVDM++仕様書生成アプローチの提案},
 volume = {49},
 year = {2020},
 yomi = {カタヤマ, テツロウ and カタヤマ, テツロウ}
}