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DocTer: documentation-guided fuzzing for testing deep learn..:
, In:
Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis
,
Xie, Danning
;
Li, Yitong
;
Kim, Mijung
... - p. 176-188 , 2022
Link:
https://dl.acm.org/doi/10.1145/3533767.3534220
RT T1 <cTitle>Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis</cTitle>: T1 <Title>DocTer: documentation-guided fuzzing for testing deep learning API functions</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3534220&Exemplar=1&LAN=DE A1 Xie, Danning A1 Li, Yitong A1 Kim, Mijung A1 Pham, Hung Viet A1 Tan, Lin A1 Zhang, Xiangyu A1 Godfrey, Michael W. PB ACM YR 2022 K1 deep learning K1 test generation K1 testing K1 text analytics K1 Software and its engineering K1 Software reliability K1 Software testing and debugging SP 176 OP 188 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3533767.3534220 DO https://dl.acm.org/doi/10.1145/3533767.3534220 SF ELIB - SuUB Bremen
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