Tool Supported Detection of Omissions by Comparing Words between Requirements and Design Document
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- Wakabayashi Takehiro
- Nagoya University
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- Morisaki Shuji
- Nagoya University
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- Kasai Norimitsu
- Communication Systems Center, Information Security Management and Investigation Department, Security Section, Mitsubishi Electric Co., Ltd.
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- Atsumi Noritoshi
- Academic Center for Computing and Media Studies, Kyoto University
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- Yamamoto Shuichiro
- Nagoya University
抄録
<p>This article proposes a tool supported approach to detect omitted requirements that are not implemented in a corresponding architectural design document using difference sets of words or word senses between a software requirements specification document and a software architectural design document. First, the proposed approach extracts sets of single-words, multi-words, and word senses that appear in a requirements specification document but do not appear in the corresponding design document using a natural language processing tool. Then, an architectural design document inspector validates whether each of the specified document with the single-words, multi-words, or word senses are implemented in the corresponding architectural design document using the sets as guides. Evaluation 1 investigated whether omitted requirements can be detected in design documents using the proposed approach. Evaluation 2 investigated the numbers of words that inspectors need to check for the proposed approach. The result of Evaluation 1 shows that omitted requirements are detected in all three pairs for real requirements specification documents and design documents. The result of Evaluation 2 shows that the numbers of words in the difference sets to those in the requirements specification documents vary from 18 to 83 % for the nine pairs of requirements specification documents and design documents.</p>
収録刊行物
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- Journal of Information Processing
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Journal of Information Processing 28 (0), 136-149, 2020
一般社団法人 情報処理学会
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キーワード
詳細情報 詳細情報について
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- CRID
- 1390846609805575936
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- NII論文ID
- 130007798627
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- ISSN
- 18826652
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可