Performance-Aware Approach for Software Risk Management Using Random Forest Algorithm

View Sample PDF

Author(s): Alankrita Aggarwal (IKG Punjab Technical University, India), Kanwalvir Singh Dhindsa (Baba Banda Singh Bahadur Engineering College, India)and P. K. Suri (Kurukshetra University, India)
Copyright: 2021
Volume: 9
Issue: 1
Pages: 8
Source title: International Journal of Software Innovation (IJSI)
Editor(s)-in-Chief: Roger Y. Lee (Central Michigan University, USA)and Lawrence Chung (The University of Texas at Dallas, USA)
DOI: 10.4018/IJSI.2021010102

Keywords: Computer Science & IT / Information Science Reference / Systems & Software Design / Systems and Software Engineering

Purchase

View Performance-Aware Approach for Software Risk Management Using Random Forest Algorithm on the publisher's website for pricing and purchasing information.

Abstract

Software quality assurance and related methodologies are quite prominent before actual launching the application so that any type of issues can be resolved at prior notifications. The process of software evaluation is one of the key tasks that are addressed by the quality assurance teams so that the risks in the software suite can be identified and can be removed with prior notifications. Different types of metrics can be used in defect prediction model and widely used metrics are source code and process metrics. The focus of this research manuscript is to develop a narrative architecture and design for software risk management using soft computing in integration with the proposed approach of random forest approach is expected to have the effectual results on multiple parameters with the flavor of multiple decision trees. The proposed approach is integrated with the framework of meta-heuristics with random forest in different substances and elements to produce a new substance.

The IRMA Community

Research IRM

Performance-Aware Approach for Software Risk Management Using Random Forest Algorithm

Purchase

Abstract

Related Content

IRMA Sponsors