LEADER 01846nam 2200373 450 001 9910172607403321 005 20230420154142.0 010 $a1-5090-6597-0 035 $a(CKB)3710000001362013 035 $a(NjHacI)993710000001362013 035 $a(EXLCZ)993710000001362013 100 $a20230420d2017 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a2017 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE) /$fInstitute of Electrical and Electronics Engineers (IEEE) 210 1$aPiscataway, New Jersey :$cInstitute of Electrical and Electronics Engineers (IEEE),$d2017. 215 $a1 online resource (various pagings) $cillustrations 311 $a1-5090-6598-9 330 $aThe aim of the workshop is to provide a forum for researchers and practitioners to present and discuss new ideas, trends and results concerning applying ML to software quality evaluation We expect that the workshop will help in (1) validation of existing and exploring new applications of ML, (2) comparing their efficiency and effectiveness, both among other automated approaches and the human judgment, and (3) adapting ML approaches already used in other areas of science. 517 $a2017 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation 606 $aComputer software$xEvaluation$vCongresses 606 $aMachine learning$vCongresses 615 0$aComputer software$xEvaluation 615 0$aMachine learning 676 $a005 801 0$bNjHacI 801 1$bNjHacl 906 $aPROCEEDING 912 $a9910172607403321 996 $a2017 IEEE Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE)$92509045 997 $aUNINA