Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Propagating frugal user feedback through closeness of code dependencies to improve IR-based traceability recovery.

H. Gao, H. Kuang, X. Ma, H. Hu, J. Lü, P. Mäder, and A. Egyed. Empir. Softw. Eng., 27 (2): 41 (2022)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

No persons found for author name Kuang, Hongyu

add a person with the name Kuang, Hongyu

Other publications of authors with the same name

Macro Action Selection with Deep Reinforcement Learning in StarCraft.S. Xu, H. Kuang, Z. Zhi, R. Hu, Y. Liu, and H. Sun. AIIDE, page 94-99. AAAI Press, (2019)Can method data dependencies support the assessment of traceability between requirements and source code?H. Kuang, P. Mäder, H. Hu, A. Ghabi, L. Huang, J. Lü, and A. Egyed. Journal of Software: Evolution and Process, 27 (11): 838-866 (2015)Do data dependencies in source code complement call dependencies for understanding requirements traceability?H. Kuang, P. Mäder, H. Hu, A. Ghabi, L. Huang, J. Lv, and A. Egyed. ICSM, page 181-190. IEEE Computer Society, (2012)Propagating frugal user feedback through closeness of code dependencies to improve IR-based traceability recovery.H. Gao, H. Kuang, X. Ma, H. Hu, J. Lü, P. Mäder, and A. Egyed. Empir. Softw. Eng., 27 (2): 41 (2022)Response Time Aware Operator Placement for Complex Event Processing in Edge Computing.X. Cai, H. Kuang, H. Hu, W. Song, and J. Lü. ICSOC, volume 11236 of Lecture Notes in Computer Science, page 264-278. Springer, (2018)Analyzing closeness of code dependencies for improving IR-based Traceability Recovery.H. Kuang, J. Nie, H. Hu, P. Rempel, J. Lu, A. Egyed, and P. Mäder. SANER, page 68-78. IEEE Computer Society, (2017)Macro action selection with deep reinforcement learning in StarCraft.S. Xu, H. Kuang, Z. Zhuang, R. Hu, Y. Liu, and H. Sun. CoRR, (2018)Using frugal user feedback with closeness analysis on code to improve IR-based traceability recovery.H. Kuang, H. Gao, H. Hu, X. Ma, J. Lu, P. Mäder, and A. Egyed. ICPC, page 369-379. IEEE / ACM, (2019)Parallelized Mobility-Aware Complex Event Processing.Y. Gong, H. Kuang, X. Cai, H. Hu, W. Song, and J. Lu. ICWS, page 898-901. IEEE, (2017)

PUMA

Disambiguation of "Kuang, Hongyu"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Propagating frugal user feedback through closeness of code dependencies to improve IR-based traceability recovery.

Please choose a person to relate this publication to

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Kuang, Hongyu"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Propagating frugal user feedback through closeness of code dependencies to improve IR-based traceability recovery.

Please choose a person to relate this publication to

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Propagating frugal user feedback through closeness of code dependencies to improve IR-based traceability recovery.