Software Defects Identification: Results Using Machine Learning and Explainable Artificial Intelligence Techniques-Reference-Cited by-同舟云学术

Software Defects Identification: Results Using Machine Learning and Explainable Artificial Intelligence Techniques

Published:2023 Issue: Volume:11 Page:132750-132765
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Begum Momotaz¹^ORCID,Shuvo Mehedi Hasan¹^ORCID,Ashraf Imran²,Mamun Abdullah Al¹^ORCID,Uddin Jia³^ORCID,Samad Md Abdus²^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Dhaka University of Engineering and Technology (DUET), Gazipur, Bangladesh

2. Department of Information and Communication Engineering, Yeungnam University, Gyeongsangbuk-do, South Korea

3. AI and Big Data Department, Endicott College, Woosong University, Daejeon, South Korea

Funder

Woosong University Academic Research 2023

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/ielx7/6287639/10005208/10304128.pdf?arnumber=10304128

Reference40 articles.

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4. Application of gradient boosting regression model for the evaluation of feature selection techniques in improving reservoir characterisation predictions

5. Long short-term memory (LSTM) networks based software fault prediction using data transformation methods

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