IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Quantitative Function for Estimating the Comparative Values of Software Test Cases

A Quantitative Function for Estimating the Comparative Values of Software Test Cases
View Sample PDF
Author(s): Yao Shi (University of North Carolina Wilmington, USA), Mark L. Gillenson (University of Memphis, USA)and Xihui Zhang (University of North Alabama, USA)
Copyright: 2022
Volume: 33
Issue: 1
Pages: 33
Source title: Journal of Database Management (JDM)
Editor(s)-in-Chief: Keng Siau (City University of Hong Kong, Hong Kong SAR)
DOI: 10.4018/JDM.299559

Purchase

View A Quantitative Function for Estimating the Comparative Values of Software Test Cases on the publisher's website for pricing and purchasing information.

Abstract

Software testing is becoming more critical to ensure that software functions properly. As the time, effort, and funds invested in software testing activities have been increased significantly, these resources still cannot meet the increasing demand of software testing. Managers must allocate testing resources to the test cases effectively in uncovering important defects. This study builds a value function that can quantify the relative value of a test case and thus play a significant role in prioritizing test cases, addressing the resource constraint issues in software testing and serving as a foundation of AI for software testing. The authors conducted a Monte Carlo simulation to exhibit application of the final value function.

Related Content

Pasi Raatikainen, Samuli Pekkola, Maria Mäkelä. © 2024. 30 pages.
Zhongliang Li, Yaofeng Tu, Zongmin Ma. © 2024. 25 pages.
Zongmin Ma, Daiyi Li, Jiawen Lu, Ruizhe Ma, Li Yan. © 2024. 32 pages.
Lavlin Agrawal, Pavankumar Mulgund, Raj Sharman. © 2024. 37 pages.
Jizi Li, Xiaodie Wang, Justin Z. Zhang, Longyu Li. © 2024. 34 pages.
Amit Singh, Jay Prakash, Gaurav Kumar, Praphula Kumar Jain, Loknath Sai Ambati. © 2024. 25 pages.
Ruizhe Ma, Weiwei Zhou, Zongmin Ma. © 2024. 21 pages.
Body Bottom