Qin, Yihao
220  results:
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2

An Extensive Study of the Structure Features in Transformer..:

, In: 2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC),
Yang, Kang ; Mao, Xinjun ; Wang, Shangwen... - p. 89-100 , 2023
 
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3

Numerical Simulation of Fully Coupled Flow-Field and Operat..:

Cao, Yihua ; Qin, Yihao ; Tan, Wenyuan.
Journal of Marine Science and Engineering.  10 (2022)  10 - p. 1455 , 2022
 
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4

Peeler: Learning to Effectively Predict Flakiness without R..:

, In: 2022 IEEE International Conference on Software Maintenance and Evolution (ICSME),
Qin, Yihao ; Wang, Shangwen ; Liu, Kui... - p. 257-268 , 2022
 
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5

Survey on recursive statistical process monitoring methods:

Wang, Youqing ; Qin, Yihao ; Lou, Zhijiang.
The Canadian Journal of Chemical Engineering.  100 (2022)  9 - p. 2093-2103 , 2022
 
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8

Modeling and Simulation of Ship–Helicopter Dynamic Interfac..:

Cao, Yihua ; Qin, Yihao
Archives of Computational Methods in Engineering.  30 (2022)  1 - p. 573-613 , 2022
 
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9

Peculiar: Smart Contract Vulnerability Detection Based on C..:

, In: 2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE),
Wu, Hongjun ; Zhang, Zhuo ; Wang, Shangwen... - p. 378-389 , 2021
 
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Automated patch correctness assessment : how far are we?:

, In: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering,
Wang, Shangwen ; Wen, Ming ; Lin, Bo... - p. 968-980 , 2020
 
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12

PEELER: Learning to Effectively Predict Flakiness without R..:

Qin, Yihao ; Wang, Shangwen ; Liu, Kui...
38th IEEE International Conference on Software Maintenance and Evolution, Limassol, Cyprus (from 02-10-2022 to 07-10-2022).  , 2022
 
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15

A fine-grained data set and analysis of tangling in bug fix..:

Herbold, Steffen ; Trautsch, Alexander ; Ledel, Benjamin...
Herbold , S , Trautsch , A , Ledel , B , Aghamohammadi , A , Ghaleb , T A , Chahal , K K , Bossenmaier , T , Nagaria , B , Makedonski , P , Ahmadabadi , M N , Szabados , K , Spieker , H , Madeja , M , Hoy , N , Lenarduzzi , V , Wang , S , Rodríguez-Pérez , G , Colomo-Palacios , R , Verdecchia , R , Singh , P , Qin , Y , Chakroborti , D , Davis , W , Walunj , V , Wu , H , Marcilio , D , Alam , O , Aldaeej , A , Amit , I , Turhan , B , Eismann , S , Wickert , A K , Malavolta , I , Sulír , M , Fard , F , Henley , A Z , Kourtzanidis , S , Tuzun , E , Treude , C , Shamasbi , S M , Pashchenko , I , Wyrich , M , Davis , J , Serebrenik , A , Albrecht , E , Aktas , E U , Strüber , D & Erbel , J 2022 , ' A fine-grained data set and analysis of tangling in bug fixing commits ' , Empirical Software Engineering , vol. 27 , no. 6 , 125 . https://doi.org/10.1007/s10664-021-10083-5.  , 2022
 
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