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Chao Ni
Chao Ni
在 zju.edu.cn 的电子邮件经过验证 - 首页
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引用次数
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An empirical study on pareto based multi-objective feature selection for software defect prediction
C Ni, X Chen, F Wu, Y Shen, Q Gu
Journal of Systems and Software 152, 215-238, 2019
1022019
Software defect number prediction: Unsupervised vs supervised methods
X Chen, D Zhang, Y Zhao, Z Cui, C Ni
Information and Software Technology 106, 161-181, 2019
962019
A cluster based feature selection method for cross-project software defect prediction
C Ni, WS Liu, X Chen, Q Gu, DX Chen, QG Huang
Journal of Computer Science and Technology 32, 1090-1107, 2017
892017
Defect detection of industry wood veneer based on NAS and multi-channel mask R-CNN
J Shi, Z Li, T Zhu, D Wang, C Ni
Sensors 20 (16), 4398, 2020
872020
Survey of static software defect prediction
陈翔, 顾庆, 刘望舒, 刘树龙, 倪超
Journal of Software 27 (1), 1-25, 2015
792015
Revisiting supervised and unsupervised methods for effort-aware cross-project defect prediction
C Ni, X Xia, D Lo, X Chen, Q Gu
IEEE Transactions on Software Engineering 48 (3), 786-802, 2020
712020
A survey on cross-project software defect prediction methods
X Chen, LP Wang, Q Gu, Z Wang, C Ni, WS Liu, Q Wang
chinese journal of computers 41 (1), 254-274, 2018
382018
FeSCH: a feature selection method using clusters of hybrid-data for cross-project defect prediction
C Ni, W Liu, Q Gu, X Chen, D Chen
2017 IEEE 41st annual computer software and applications conference (COMPSAC …, 2017
362017
The best of both worlds: integrating semantic features with expert features for defect prediction and localization
C Ni, W Wang, K Yang, X Xia, K Liu, D Lo
Proceedings of the 30th ACM Joint European Software Engineering Conference …, 2022
262022
Revisiting heterogeneous defect prediction methods: How far are we?
X Chen, Y Mu, K Liu, Z Cui, C Ni
Information and Software Technology 130, 106441, 2021
262021
Do different crossproject defect prediction methods identify the same defective modules?
X Chen, Y Mu, Y Qu, C Ni, M Liu, T He, S Liu
Journal of Software: Evolution and Process 32 (5), e2234, 2020
212020
Cross-project defect prediction method based on feature transfer and instance transfer
倪超, 陈翔, 刘望舒, 顾庆, 黄启国, 李娜
Journal of Software 30 (5), 1308-1329, 2019
172019
Just-In-Time Defect Prediction on JavaScript Projects: A Replication Study
C NI, XIN XIA, D LO, X YANG, AE HASSAN
122021
Defect identification, categorization, and repair: Better together
C Ni, K Yang, X Xia, D Lo, X Chen, X Yang
arXiv preprint arXiv:2204.04856, 2022
102022
Multitask defect prediction
C Ni, X Chen, X Xia, Q Gu, Y Zhao
Journal of Software: Evolution and Process 31 (12), e2203, 2019
82019
Multi-project Regression based Approach for Software Defect Number Prediction.
Q Huang, C Ni, X Chen, Q Gu, K Cao
SEKE, 425-546, 2019
42019
FVA: Assessing Function-Level Vulnerability by Integrating Flow-Sensitive Structure and Code Statement Semantic
C Ni, L Shen, W Wang, X Chen, X Yin, L Zhang
2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC …, 2023
22023
Intelligent identification of film on cotton based on hyperspectral imaging and convolutional neural network
Z Liu, L Zhao, X Yu, Y Zhang, J Cui, C Ni, L Zhang
Science Progress 105 (4), 00368504221137461, 2022
22022
Code-line-level bugginess identification: How far have we come, and how far have we yet to go?
Z Guo, S Liu, X Liu, W Lai, M Ma, X Zhang, C Ni, Y Yang, Y Li, L Chen, ...
ACM Transactions on Software Engineering and Methodology 32 (4), 1-55, 2023
12023
Automatic Identification of Crash-inducing Smart Contracts
C Ni, C Tian, K Yang, D Lo, J Chen, X Yang
2023 IEEE International Conference on Software Analysis, Evolution and …, 2023
12023
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