A Survey on Deep Learning Techniques Used for Quality Process

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Author(s): Vanyashree Mardi (Alva's Institute of Engineering and Technology, India), Naresh E. (Jain University, India & Ramaiah Institute of Technology, India)and Vijaya Kumar B. P. (Ramaiah Institute of Technology, India)
Copyright: 2019
Pages: 22
Source title: Handbook of Research on Deep Learning Innovations and Trends
Source Author(s)/Editor(s): Aboul Ella Hassanien (Cairo University, Egypt), Ashraf Darwish (Helwan University, Egypt)and Chiranji Lal Chowdhary (VIT University, India)
DOI: 10.4018/978-1-5225-7862-8.ch008

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science Reference / Neural Networks

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Abstract

In the current era, software development and software quality has become extensively important for implementing the real-world software application, and it will enhance the software functionality. Moreover, early prediction of expected error and fault level in the quality process is critical to the software development process. Deep learning techniques are the most appropriate methods for this problem, and this chapter carries out an extensive systematic survey on a variety of deep learning. These techniques are used in the software quality process along with a hypothesis justification for each of the proposed solutions. The deep learning and machine learning techniques are considered to be the most suitable systems for software quality prediction. Deep learning is a computational model made up of various hidden layers of investigation used to portray of information with the goal that researchers can better understand complex information issues.

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A Survey on Deep Learning Techniques Used for Quality Process

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