Open AccessNEURAL-NETWORK MODEL OF SOFTWARE QUALITY PREDICTION BASED ON QUALITY ATTRIBUTES
Author(s) -
Mykyta Lebiga,
Tetiana Hovorushchenko,
Mariia KAPUSTIAN
Publication year - 2022
Publication title -
kompûternì sistemi ta ìnformacìjnì tehnologìï
Language(s) - English
Resource type - Journals
eISSN - 2710-0774
pISSN - 2710-0766
DOI - 10.31891/csit-2022-1-9
Subject(s) - computer science , software quality , artificial neural network , software portability , usability , software , quality (philosophy) , data mining , reliability (semiconductor) , reliability engineering , software quality control , artificial intelligence , machine learning , software development , engineering , human–computer interaction , operating system , philosophy , power (physics) , physics , epistemology , quantum mechanics
The paper proposes a neural-network model of software quality prediction based on quality attributes. The proposedmodel differs from the known models, because it provides considering the importance of each quality attribute and their interactionwithin each software quality characteristic. The artificial neural network (ANN) outputs correspond to the values of software qualitycharacteristics (functional suitability, performance efficiency, usability, reliability, compatibility, security, maintainabi lity, portability).The artificial neural network (ANN) outputs make it possible assessing the total impact of quality attributes on software qualitycharacteristics