Title: Prediction of software quality using neuro-fuzzy model

Authors: Saumendra Pattnaik; Binod Kumar Pattanayak; Srikanta Patnaik

Addresses: Department of Computer Science and Engineering, Institute of Technical Education and Research, Siksha 'O' Anusandhan University, Khandagiri, Odisha, India ' Department of Computer Science and Engineering, Institute of Technical Education and Research, Siksha 'O' Anusandhan University, Khandagiri, Odisha, India ' Department of Computer Science and Engineering, Institute of Technical Education and Research, Siksha 'O' Anusandhan University, Khandagiri, Odisha, India

Abstract: In the era of digital systems, management of software project is the biggest challenge. So, early prediction of software quality plays a vital role in the software industry. It helps the management to take the qualitative decisions. In this paper the prediction model proposed by us is a hybrid one with the combination of neural network and fuzzy logic, which discards their individual limitations. This model provides some features which are able to deal with various objectives at the time of software development process. Using this model the prediction of software quality can be measured that also helps in checking the errors and avoiding the expense of redoing.

Keywords: fuzzy logic; neural network; software engineering; software quality; LabVIEW; SPSS.

DOI: 10.1504/IJIE.2018.093426

International Journal of Intelligent Enterprise, 2018 Vol.5 No.3, pp.292 - 307

Received: 17 Jan 2018
Accepted: 22 Feb 2018
Published online: 25 Jul 2018 *

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