Early Software Defects Density Prediction: Training the International Software Benchmarking Cross Projects Data Using Supervised Learning-Reference-Cited by-同舟云学术

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Early Software Defects Density Prediction: Training the International Software Benchmarking Cross Projects Data Using Supervised Learning

Published:2023 Issue: Volume:11 Page:141965-141986
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tahir Touseef¹^ORCID,Gencel Cigdem²^ORCID,Rasool Ghulam¹^ORCID,Umer Tariq¹^ORCID,Rasheed Jawad³^ORCID,Yeo Sook Fern⁴^ORCID,Cevik Taner⁵

Affiliation:

1. Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Lahore, Pakistan

2. Department of Management Information Systems, Ankara Medipol University, Ankara, Turkey

3. Department of Computer Engineering, Istanbul Sabahattin Zaim University, İstanbul, Turkey

4. Faculty of Business, Multimedia University, Malacca, Malaysia

5. Department of Computer Engineering, Istanbul Arel University, İstanbul, Turkey

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10345541.pdf?arnumber=10345541

Reference42 articles.

1. Multiobjective Testing Resource Allocation Under Uncertainty

2. Understanding and controlling software costs

3. On the relative value of cross-company and within-company data for defect prediction

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