An analytical study on testing metrics for software applications

Authors

  • Kamal Kant Sharma KIET Group of Institutions, Ghaziabad
  • Amit Sinha ABES Engineering College
  • Arun Sharma Indira Gandhi Delhi Technical University for Women

Keywords:

Machine Learning, Mobile Applications, Software Reliability, Artificial Intelligence

Abstract

In day-to-day life, software applications have acquired an important part. Some of these applications are open source and some are paid ones. Majority of Users mainly search for free, error-free apps that can meet their requirements. So, to make error free applications, proper testing is required which requires more time and efforts. Similar to desktop applications, black box or white box testing can be applied to mobile applications too. The main objective of this paper is to review on different testing methods used for testing mobile applications, web applications or artificial intelligence applications. The paper reviewed and analyzed the recent contributions of researchers using machine learning approach for testing software applications and identified the limitations and future research scope in this field.

URN:NBN:sciencein.jist.2023.v11.517

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Software testing using Machine Learning

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Published

2023-01-20

Issue

Section

Computer Sciences and Mathematics

URN

How to Cite

An analytical study on testing metrics for software applications. (2023). Journal of Integrated Science and Technology, 11(3), 517. https://pubs.thesciencein.org/journal/index.php/jist/article/view/517

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