NEURAL-NETWORK MODEL OF SOFTWARE QUALITY PREDICTION BASED ON QUALITY ATTRIBUTES

Authors

  • MYKYTA LEBIGA Khmelnytskyi National University
  • TETIANA HOVORUSHCHENKO Khmelnytskyi National University
  • MARIIA KAPUSTIAN Khmelnytskyi National University

DOI:

https://doi.org/10.31891/CSIT-2022-1-9

Keywords:

software, software quality, software quality attributes, software quality characteristics, artificial neural network (ANN)

Abstract

The paper proposes a neural-network model of software quality prediction based on quality attributes. The proposed
model differs from the known models, because it provides considering the importance of each quality attribute and their interaction
within each software quality characteristic. The artificial neural network (ANN) outputs correspond to the values of software quality
characteristics (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 quality
characteristics

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Published

2022-04-14

How to Cite

LEBIGA, M. ., HOVORUSHCHENKO, T. ., & KAPUSTIAN, M. . (2022). NEURAL-NETWORK MODEL OF SOFTWARE QUALITY PREDICTION BASED ON QUALITY ATTRIBUTES. Computer Systems and Information Technologies, (1), 69–74. https://doi.org/10.31891/CSIT-2022-1-9

Issue

No. 1 (2022): Computer Systems and Information Technologies

Section

Articles