Empirical evaluation of the performance of data sampling and feature selection techniques for software fault prediction-Reference-Cited by-同舟云学术

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Empirical evaluation of the performance of data sampling and feature selection techniques for software fault prediction

Published:2023-08 Issue: Volume:223 Page:119806
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Rathi Sonika Chandrakant^ORCID,Misra Sanjay^ORCID,Colomo-Palacios Ricardo^ORCID,Adarsh R.^ORCID,Neti Lalita Bhanu Murthy^ORCID,Kumar Lov^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference63 articles.

1. Semi-supervised deep fuzzy c-mean clustering for software fault prediction;Arshad;IEEE Access,2018

2. Experimental validation of inheritance metrics’ impact on software fault prediction;Aziz;IEEE Access,2019

3. Data sampling-based feature selection framework for software defect prediction;Balogun,2020

4. A validation of object-oriented design metrics as quality indicators;Basili;IEEE Transactions on Software Engineering,1996

5. A study on modeling techniques in software fault prediction;Bhandari,2021

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1. WSO-KELM: War Strategy Optimization-Based Kernel Extreme Learning Machine for Automatic Software Fault Prediction Model;Journal of The Institution of Engineers (India): Series B;2024-06-13

2. Feature Selection using Genetic Algorithm for Software Fault Prediction;2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2024-06-05

3. Graph-Driven Exploration of Issue Handling Schemes in Software Projects;Applied Sciences;2024-05-30

4. A software defect prediction method based on learnable three-line hybrid feature fusion;Expert Systems with Applications;2024-04

5. Sahand: A Software Fault-Prediction Method Using Autoencoder Neural Network and K-Means Algorithm;Journal of Electronic Testing;2024-04

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