Article (Scientific journals)
Test Selection for Deep Learning Systems
Ma, Wei; Papadakis, Mike; Tsakmalis, Anestis et al.
2021In ACM Transactions on Software Engineering and Methodology, 30 (2), p. 13:1--13:22
Peer Reviewed verified by ORBi
 

Files


Full Text
0-tosem (1).pdf
Author preprint (1.09 MB)
Download

All documents in ORBilu are protected by a user license.

Send to



Details



Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Security Design and Validation Research Group (SerVal)
Disciplines :
Computer science
Author, co-author :
Ma, Wei ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Papadakis, Mike ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
Tsakmalis, Anestis
Cordy, Maxime  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Le Traon, Yves ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)
External co-authors :
no
Language :
English
Title :
Test Selection for Deep Learning Systems
Publication date :
2021
Journal title :
ACM Transactions on Software Engineering and Methodology
ISSN :
1049-331X
Publisher :
Association for Computing Machinery (ACM), United States
Volume :
30
Issue :
2
Pages :
13:1--13:22
Peer reviewed :
Peer Reviewed verified by ORBi
FnR Project :
FNR11686509 - Continuous Development With Mutation Analysis And Testing, 2017 (01/09/2018-31/08/2021) - Michail Papadakis
Name of the research project :
CODEMATES
Funders :
FNR - Fonds National de la Recherche [LU]
Available on ORBilu :
since 25 October 2020

Statistics


Number of views
613 (87 by Unilu)
Number of downloads
311 (42 by Unilu)

Scopus citations®
 
41
Scopus citations®
without self-citations
35
OpenCitations
 
14
WoS citations
 
39

Bibliography


Similar publications



Contact ORBilu