Presentation 2021-03-06
Software Bug Severity Prediction with BERT
Tomoki Yamada, Takako Nakatani,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This paper aims to automatically assess the severity of software bug reports issued from a large-scale enterprise system construction using BERT. Automatic assessment of bug severity improves the quality of software as well as reduces the cost of development. The targeted bug reports are relatively small (around 10000) and written in Japanese, though the major preceding studies conducted the similar classification on the massive sets (>100000) of bug reports in English from open source software. In addition, unlike preceding studies that commonly used meta-data of bugs as explanatory variables, the proposed classification model is simply based on the bug description text. The result shows that the accuracy of the BERT-based model is as high as the preceding studies, though the size of data is far smaller.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) BERT / Bug Triage / Severity Prediction / Software Development / arge-scale Enterprise System / L
Paper # KBSE2020-47
Date of Issue 2021-02-26 (KBSE)

Conference Information
Committee KBSE
Conference Date 2021/3/5(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Hiroyuki Nakagawa(Osaka Univ.)
Vice Chair Takuya Saruwatari(NTT Data)
Secretary Takuya Saruwatari(OKI)
Assistant Shinpei Ogata(Shinshu Univ.) / Erina Nakihara(Doshisha Univ,)

Paper Information
Registration To Technical Committee on Knowledge-Based Software Engineering
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Software Bug Severity Prediction with BERT
Sub Title (in English) Case Study on a Large-scale Enterprise System
Keyword(1) BERT
Keyword(2) Bug Triage
Keyword(3) Severity Prediction
Keyword(4) Software Development
Keyword(5) arge-scale Enterprise System
Keyword(6) L
1st Author's Name Tomoki Yamada
1st Author's Affiliation Open University of Japan(OUJ)
2nd Author's Name Takako Nakatani
2nd Author's Affiliation Open University of Japan(OUJ)
Date 2021-03-06
Paper # KBSE2020-47
Volume (vol) vol.120
Number (no) KBSE-423
Page pp.pp.77-82(KBSE),
#Pages 6
Date of Issue 2021-02-26 (KBSE)