Presentation 2022-07-15
A Method for Selecting Training Data using Topic Models and Doc2Vec for Automatic Test Cases Generation
Yuto Fujita, Kiyoshi Ueda,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In the development of large-scale communication software, due to the increase in development cost and shortage of manpower, a method to automatically generate test cases of system testing from requirement specifications using machine learning has been studied. In this study, we improve the accuracy of automatic test item generation by selecting requirement specifications for machine learning training data. Each requirement specification is vectorized using topic models (LSA, LDA) and Doc2Vec, and the similarity between each requirement specification vector is calculated. We propose a method to select specifications with high similarity to the requirement specifications of test data and use them as training data. We evaluate the effectiveness of the proposed method by measuring the percentage of correct answers using the proposed method on requirement specifications of large-scale communication software.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Large-scale Communication Software / Automatic Test Cases Generation / Machine Learning / Topic Model / Doc2Vec
Paper # NS2022-52
Date of Issue 2022-07-06 (NS)

Conference Information
Committee NS / SR / RCS / SeMI / RCC
Conference Date 2022/7/13(3days)
Place (in Japanese) (See Japanese page)
Place (in English) The Kanazawa Theatre + Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Distributed Wireless Network, M2M (Machine-to-Machine),D2D (Device-to-Device),IoT(Internet of Things), etc
Chair Tetsuya Oishi(NTT) / Suguru Kameda(Hiroshima Univ.) / Kenichi Higuchi(Tokyo Univ. of Science) / Koji Yamamoto(Kyoto Univ.) / Shunichi Azuma(Nagoya Univ.)
Vice Chair Takumi Miyoshi(Shibaura Insti of Tech.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) / Kazuto Yano(ATR) / Tomoya Tandai(Toshiba) / Fumihide Kojima(NICT) / Osamu Muta(Kyushu Univ.) / Kazuya Monden(Hitachi) / Yasunori Owada(NICT) / Shunsuke Saruwatari(Osaka Univ.) / Shunichi Azuma(Hokkaido Univ.) / Koji Ishii(Kagawa Univ.)
Secretary Takumi Miyoshi(NTT) / Osamu Takyu(Kogakuin Univ.) / Kentaro Ishidu(Mie Univ.) / Kazuto Yano(Tokai Univ.) / Tomoya Tandai(NTT) / Fumihide Kojima(Panasonic) / Osamu Muta(Univ. of Electro-Comm) / Kazuya Monden(Sharp) / Yasunori Owada(NTT DOCOMO) / Shunsuke Saruwatari(Tokyo Univ. of Agri. and Tech.) / Shunichi Azuma(Osaka Univ.) / Koji Ishii(CRIEPI)
Assistant Kotaro Mihara(NTT) / Taichi Ohtsuji(NEC) / WANG Xiaoyan(Ibaraki Univ.) / Akemi Tanaka(MathWorks) / Katsuya Suto(Univ. of Electro-Comm) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) / Issei Kanno(KDDI Research) / Yuyuan Chang(Tokyo Inst. of Tech) / Yuki Matsuda(NAIST) / Akihito Taya(Aoyama Gakuin Univ.) / Takeshi Hirai(Osaka Univ.) / SHAN LIN(NICT) / Ryosuke Adachi(Yamaguchi Univ.)

Paper Information
Registration To Technical Committee on Network Systems / Technical Committee on Smart Radio / Technical Committee on Radio Communication Systems / Technical Committee on Sensor Network and Mobile Intelligence / Technical Committee on Reliable Communication and Control
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Method for Selecting Training Data using Topic Models and Doc2Vec for Automatic Test Cases Generation
Sub Title (in English)
Keyword(1) Large-scale Communication Software
Keyword(2) Automatic Test Cases Generation
Keyword(3) Machine Learning
Keyword(4) Topic Model
Keyword(5) Doc2Vec
1st Author's Name Yuto Fujita
1st Author's Affiliation Nihon University(Nihon Univ.)
2nd Author's Name Kiyoshi Ueda
2nd Author's Affiliation Nihon University(Nihon Univ.)
Date 2022-07-15
Paper # NS2022-52
Volume (vol) vol.122
Number (no) NS-105
Page pp.pp.121-126(NS),
#Pages 6
Date of Issue 2022-07-06 (NS)