Application of machine learning paradigms for predicting quality in upstream software development life cycle

DOI10.1007/BF03398746zbMath1161.68733OpenAlexW2779756973WikidataQ122484679 ScholiaQ122484679MaRDI QIDQ1018940

J. Martínez

Publication date: 26 May 2009

Published in: Opsearch (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf03398746

zbMATH Keywords

genetic algorithmmachine learningartificial neural networkrule inductioncase based reasoningsoftware quality

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Reliability, testing and fault tolerance of networks and computer systems (68M15)

Cites Work

• A logical calculus of the ideas immanent in nervous activity
• Unnamed Item

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