コンテンツへスキップ
2024 年
国際会議 （査読あり）
Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa, and Minoru Kawahara,A Quantitative Investigation of Trends in Confusing Variable Pairs Through Commits: Do Confusing Variable Pairs Survive? ,”
Kaoru Yokogawa, Masashi Hiroishi, Sousuke Amasaki, Hirohisa Aman, and Tomoyuki Yokogawa,
Pattara Leelaprute, Yuki Kase, Sousuke Amasaki, Hirohisa Aman, and Tomoyuki Yokogawa,
Yahiro Mori, Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa, and Minoru Kawahara,
Shozo Saeki, Minoru Kawahara and Hirohisa Aman,Multi-attribute and Multi-label Deep Metric Learning via Pair-based and Proxy-based Losses ,”
2023 年
論文誌 （査読あり）
Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa, and Minoru Kawahara,An Automated Detection of Confusing Variable Pairs with Highly Similar Compound Names in Java and Python Programs ,”
Hideyoshi Miura, Tomotaka Kimura, Hirohisa Aman, Kouji Hirata,Game-theoretic approach to epidemic modeling of countermeasures against future malware evolution ,”
Shozo Saeki, Minoru Kawahara, Hirohisa Aman,Multi proxy anchor family loss for several types of gradients ,”
Kosuke Ohara, Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa, and Minoru Kawahara,A Comparative Study of Data Collection Periods for Just-In-Time Defect Prediction Using the Automatic Machine Learning Method ,”
国際会議 （査読あり）
Yuki Fushihara, Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa, and Minoru Kawahara,A Trend Analysis of Test Smells in Python Test Code Over Commit History ,”accepted version 実験データ ]
Shinnosuke Irie, Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa and Minoru Kawahara,A Comparative Study of Hybrid Fault-Prone Module Prediction Models Using Association Rule and Random Forest ,”
ワークショップ （査読あり）
大嶋 琉太，阿萬 裕久，川原 稔，【IEEE Computer Society Japan Chapter FOSE Young Researcher Award 受賞】 【FOSE2023貢献賞を受賞】
髙橋 佑介，阿萬 裕久，川原 稔，
水本 拓海，横川 智教，天嵜 聡介，阿萬 裕久，有本 和民，
伏原 裕生，阿萬 裕久，川原 稔，
森 哉尋，阿萬 裕久，川原 稔，
2022 年
論文誌 （査読あり）
峯久 朋也，阿萬 裕久，川原 稔，Transformer によるメソッド名推定を活用したネーミングバグの検出 ,”
Sousuke Amasaki, Hirohisa Aman and Tomoyuki Yokogawa,An extended study on applicability and performance of homogeneous cross-project defect prediction approaches under homogeneous cross-company effort estimation situation ,”
国際会議 （査読あり）
Sousuke Amasaki, Hirohisa Aman and Tomoyuki Yokogawa,An Evaluation of Cross-Project Defect Prediction Approaches on Cross-Personalized Defect Prediction ,”
Kazuki Wayama, Tomoyuki Yokogawa, Sousuke Amasaki, Hirohisa Aman, Kazutami Arimoto,Verifying Game Logic in Unreal Engine 5 Blueprint Visual Scripting System Using Model Checking ,”
Tenma Kita, Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa, and Minoru Kawahara,Have Java Production Methods Co-Evolved With Test Methods Properly?: A Fine-Grained Repository-Based Co-Evolution Analysis ,”accepted version 実験データ ]
Sousuke Amasaki, Hirohisa Aman, and Tomoyuki Yokogawa,An Evaluation of Effort-Aware Fine-Grained Just-in-Time Defect Prediction Methods ,”
Kazuma Toyota, Tomoyuki Yokogawa, Sousuke Amasaki, Hirohisa Aman and Kazutami Arimoto,A Visual Modeling Environment for the nuXmv Model Checker Intended for Novice Users ,”
ワークショップ （査読あり）
大嶋 琉太，阿萬 裕久，川原 稔，プログラムのベクトル化と記号実行を活用した正誤判定の効率化 ,”
メソッド名の整合性評価のためのデータセット ,”
研究会
高橋 佑介，阿萬 裕久，川原 稔，【ポスター・デモ賞を受賞】
高橋 亮至，阿萬 裕久，川原 稔，Pycodestyleによる警告とバグ修正の関係に関する定量分析 ，”
峯久 朋也，阿萬 裕久，川原 稔，
2021 年
論文誌 （査読あり）
山中 啓太，阿萬 裕久，川原 稔，プログラムスライスと Doc2Vec を用いた変数名評価法の提案 ，”
国際会議 （査読あり）
Sousuke Amasaki, Hirohisa Aman and Tomoyuki Yokogawa,Searching for Bellwether Developers for Cross-Personalized Defect Prediction ,”
Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa and Minoru Kawahara,An Investigation of Compound Variable Names Toward Automated Detection of Confusing Variable Pairs ,”accepted version 実験データ ]
Hirohisa Aman, Sousuke Amasaki, Tomoyuki Yokogawa and Minoru Kawahara,A Large-Scale Investigation of Local Variable Names in Java Programs: Is Longer Name Better for Broader Scope Variable? ,”実験データ ]
Sousuke Amasaki, Hirohisa Aman and Tomoyuki Yokogawa,A Preliminary Evaluation of CPDP Approaches on Just-in-Time Software Defect Prediction ,”
Tomoya Minehisa, Hirohisa Aman, Tomoyuki Yokogawa and Minoru Kawahara,A Comparative Study of Vectorization Approaches for Detecting Inconsistent Method Names ,”【Best Student Paper Award 受賞 】
Shozo Saeki, Minoru Kawahara and Hirohisa Aman,Significance of Emphasized Features for Good Representation on Deep Metric Learning ,”
ワークショップ （査読あり）
峯久 朋也，阿萬 裕久，川原 稔，ソースコードの難読化解除手法を活用したメソッド名の整合性評価 ,” 【IEEE Computer Society Japan Chapter FOSE Young Researcher Award 受賞】
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