Developing a quality software product is an essential need of the software industry. Software quality comprises of various factors. Therefore, it cannot be measured on the basis of a single variable. Several agile software development methods have evolved all around the world with the passage of time that contribute towards the development of new and improved software methods. The agile processes have started invading the software development industry to provide good quality software in minimal time. As the changes have occurred in the modern day evaluation metrics, the changes have been observed in the agile oriented quality evaluation methods as well. This paper presents a machine learning based approach for evaluating agile based methods for enhancing software quality. This advanced mechanism of processing the data attributes is inspired by SWARA and FDD. The validation and evaluation has been done using statistical and the quantitative parameters.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.