Open AccessSoftware Quality Prediction Method Using Fuzzy Logic
Author(s) -
et. al. Ritu
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i11.5966
Subject(s) - maintainability , computer science , software quality , software portability , fuzzy logic , software sizing , data mining , software , quality (philosophy) , identification (biology) , verification and validation , software metric , usability , software development , reliability engineering , soft computing , software construction , software engineering , machine learning , artificial intelligence , operating system , engineering , philosophy , operations management , botany , epistemology , biology
: Software Quality is the key priority of today’s marketplace and software development organization to which a system, technique, or factor meets particular requirements and conditions. Soft computing techniques play a vital role in developing software engineering applications. In this paper, we have identified five parameters: Reliability, Efficiency, Usability, Maintainability, and Portability for accessing the level of quality of software. A fuzzy logic-based intelligent identification methodology has been proposed to access the quality of particular software-based on five parameters. The proposed identification scheme takes these five parameters as input and predicts the quality of the software using the fuzzy rule base which is generated using various studies. As this scheme takes five inputs and each input is divided into three regions i.e. ‘Low’, ‘Medium’, ‘High’ and thus a total of 35 i.e. 243 rules has been generated to analyze the software quality. Furthermore, Mamdani fuzzy model has been used as the reference model. To show the effectiveness of the proposed methodology, simulation results have been performed in MATLAB, which shows that the software's quality closely matches with the actual one.