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Masanari Kondo
Masanari Kondo
Verified email at ait.kyushu-u.ac.jp - Homepage
Title
Cited by
Cited by
Year
The impact of feature reduction techniques on defect prediction models
M Kondo, CP Bezemer, Y Kamei, AE Hassan, O Mizuno
Empirical Software Engineering 24, 1925-1963, 2019
1092019
Code cloning in smart contracts: a case study on verified contracts from the Ethereum blockchain platform
M Kondo, GA Oliva, ZM Jiang, AE Hassan, O Mizuno
Empirical Software Engineering 25, 4617-4675, 2020
542020
The impact of context metrics on just-in-time defect prediction
M Kondo, DM German, O Mizuno, EH Choi
Empirical software engineering 25, 890-939, 2020
452020
An empirical study on self-admitted technical debt in modern code review
Y Kashiwa, R Nishikawa, Y Kamei, M Kondo, E Shihab, R Sato, ...
Information and Software Technology 146, 106855, 2022
172022
An empirical study of utilization of imperative modules in ansible
S Kokuryo, M Kondo, O Mizuno
2020 IEEE 20Th international conference on software quality, reliability and …, 2020
152020
PAFL: Probabilistic Automaton-based Fault Localization for Recurrent Neural Networks
Y Ishimoto, M Kondo, N Ubayashi, Y Kamei
Information and Software Technology 155, 107117, 2023
42023
An empirical study of issue-link algorithms: which issue-link algorithms should we use?
M Kondo, Y Kashiwa, Y Kamei, O Mizuno
Empirical Software Engineering 27 (6), 136, 2022
42022
Do visual issue reports help developers fix bugs? a preliminary study of using videos and images to report issues on GitHub
H Kuramoto, M Kondo, Y Kashiwa, Y Ishimoto, K Shindo, Y Kamei, ...
Proceedings of the 30th IEEE/ACM International Conference on Program …, 2022
42022
Which metrics should researchers use to collect repositories: An empirical study
K Yamamoto, M Kondo, K Nishiura, O Mizuno
2020 IEEE 20th International Conference on Software Quality, Reliability and …, 2020
42020
An empirical study of source code detection using image classification
J Hong, O Mizuno, M Kondo
2019 10th International Workshop on Empirical Software Engineering in …, 2019
32019
深層学習によるソースコードコミットからの不具合混入予測
近藤将成, 森啓太, 水野修, 崔銀惠
情報処理学会論文誌 59 (4), 1250-1261, 2018
32018
Causal-Effect Analysis using Bayesian LiNGAM Comparing with Correlation Analysis in Function Point Metrics and Effort
M Kondo, O Mizuno, EH Choi
International Journal of Mathematical, Engineering and Management Sciences …, 2018
32018
Just-in-time defect prediction applying deep learning to source code changes
M KONDO, K MORI, O MIZUNO, EH CHOI
情報処理学会論文誌ジャーナル (Web) 59 (4), 1250-1261, 2018
22018
Analysis on causal-effect relationship in effort metrics using Bayesian LiNGAM
M Kondo, O Mizuno
2016 IEEE International Symposium on Software Reliability Engineering …, 2016
22016
Towards Privacy Preserving Cross Project Defect Prediction with Federated Learning
H Yamamoto, D Wang, GK Rajbahadur, M Kondo, Y Kamei, N Ubayashi
2023 IEEE International Conference on Software Analysis, Evolution and …, 2023
12023
Commit-Based Class-Level Defect Prediction for Python Projects
KY Mon, M Kondo, E Choi, O Mizuno
IEICE TRANSACTIONS on Information and Systems 106 (2), 157-165, 2023
12023
Challenges and future research direction for microtask programming in industry
M Kondo, S Saito, Y Iimura, E Choi, O Mizuno, Y Kamei, N Ubayashi
Proceedings of the 19th International Conference on Mining Software …, 2022
12022
類似した開発者の分類と不具合予測におけるその効果
北村紗也加, 近藤将成, 水野修
ソフトウェアエンジニアリングシンポジウム 2019 論文集 2019, 180-189, 2019
12019
深層学習による不具合混入コミットの予測と評価
近藤将成, 森啓太, 水野修, 崔銀惠
ソフトウェアエンジニアリングシンポジウム 2017 論文集 2017, 35-45, 2017
12017
Exploring the Effect of Multiple Natural Languages on Code Suggestion Using GitHub Copilot
K Koyanagi, D Wang, K Noguchi, M Kondo, A Serebrenik, Y Kamei, ...
arXiv preprint arXiv:2402.01438, 2024
2024
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