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Predicting metamorphic relations for testing scientific software: a machine learning approach using graph kernels
Author(s) -
Kanewala Upulee,
Bieman James M.,
BenHur Asa
Publication year - 2016
Publication title -
software testing, verification and reliability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 49
eISSN - 1099-1689
pISSN - 0960-0833
DOI - 10.1002/stvr.1594
Subject(s) - computer science , oracle , machine learning , programmer , artificial intelligence , control flow , theoretical computer science , graph , software , data mining , programming language
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