This paper is published in Volume-5, Issue-2, 2019
Area
Software Quality
Author
Anil Kumar
Org/Univ
Saroj Institute of Technology and Management, Lucknow, Uttar Pradesh, India
Pub. Date
14 March, 2019
Paper ID
V5I2-1269
Publisher
Keywords
Software quality model, Soft computing techniques, Neural Network, Fuzzy Logic

Citationsacebook

IEEE
Anil Kumar. Analysis of object-oriented system quality model using soft computing techniques, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Anil Kumar (2019). Analysis of object-oriented system quality model using soft computing techniques. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Anil Kumar. "Analysis of object-oriented system quality model using soft computing techniques." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

Quality plays very important role in software industry because the objective of every software industry is to produce good quality software with in time and budget. Number of quality models have been proposed and used by various authors to build good quality software and these software quality models are also responsible for improving the performance, this improvement directly reflects the quality, increase users satisfaction and decrease the cost of quality. This report we have discussed and compared various quality models and soft computing techniques used for predicting the quality of software product and software system. It is found from the literature that there are lots of quality models and we measure quality based on their characteristics, so here, in this work we gives the characteristics definition and then comparison of quality models related to quality characteristics. In this study we exploring the information about soft computing technique for predicting the quality of a system or product and also develop a new quality model using soft computing (Fuzzy, Neural Network and Neuro-fuzzy) approach which is responsible to predict the software quality of an object-oriented system. In this report, we also identifies the most important factors of object-oriented system like Efficiency, Reliability, Reusability and Maintainability and also proposed a model based on these four factors that evaluating the quality of object-oriented system using soft computing technique i.e. Fuzzy Logic, Neural Network and Neuro-Fuzzy.
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