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Automatic Classifying Self-Admitted Technical Debt Using N-Gram IDF

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dc.contributor.author Supatsara, Wattanakriengkrai en
dc.contributor.author Napat, Srisermphoak en
dc.contributor.author Sahawat, Sintoplertchaikul en
dc.contributor.author Morakot l, Choetkiertiku en
dc.contributor.author Chaiyong, Ragkhitwetsagul en
dc.contributor.author Thanwadee, Sunetnanta en
dc.contributor.author Hata, Hideaki en
dc.contributor.author Matsumoto, Kenichi en
dc.date.accessioned 2020-02-03T08:33:23Z en
dc.date.available 2020-02-03T08:33:23Z en
dc.date.issued 2019-12-05 en
dc.identifier.issn 2640-0715 en
dc.identifier.uri http://hdl.handle.net/10061/13964 en
dc.description 2019 26th Asia-Pacific Software Engineering Conference (APSEC) ,Putrajaya, Malaysia, en
dc.description.abstract Technical Debt (TD) introduces a quality problem and increases maintenance cost since it may require improvements in the future. Several studies show that it is possible to automatically detect TD from source code comments that developers intentionally created, so-called self-admitted technical debt (SATD). Those studies proposed to use binary classification technique to predict whether a comment shows SATD. However, SATD has different types (e.g. design SATD and requirement SATD). In this paper, we therefore propose an approach using N-gram Inverse Document Frequency (IDF) and employ a multi-class classification technique to build a model that can identify different types of SATD. From the empirical evaluation on 10 open-source projects, our approach outperforms alternative methods (e.g. using BOW and TF-IDF). Our approach also improves the prediction performance over the baseline benchmark by 33% en
dc.description.sponsorship This work has been supported by JSPS KAKENHI (Grant Number 16H05857 and 17H00731). en
dc.language.iso en en
dc.publisher IEEE en
dc.rights ©2019 IEEE ja
dc.rights 出版社許諾条件により、本文は2021年12月6日以降に公開 ja
dc.subject Self Admitted Technical Debt en
dc.subject N-Gram IDF en
dc.subject Multi class Classification en
dc.title Automatic Classifying Self-Admitted Technical Debt Using N-Gram IDF en
dc.type.nii Conference Paper en
dc.contributor.transcription ハタ, ヒデアキ ja
dc.contributor.transcription マツモト, ケンイチ ja
dc.contributor.alternative 畑, 秀明 ja
dc.contributor.alternative 松本, 健一 ja
dc.textversion author en
dc.identifier.spage 316 en
dc.identifier.epage 322 en
dc.relation.doi 10.1109/APSEC48747.2019.00050 en
dc.identifier.NAIST-ID 73299364 en
dc.identifier.NAIST-ID 73292310 en


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