Data quality issues in software fault prediction: a systematic literature review

K Bhandari, K Kumar, AL Sangal - Artificial Intelligence Review, 2023 - Springer
Software fault prediction (SFP) aims to improve software quality with a possible minimum
cost and time. Various machine learning models have been proposed in the past for …

Software defect prediction based on enhanced metaheuristic feature selection optimization and a hybrid deep neural network

K Zhu, S Ying, N Zhang, D Zhu - Journal of Systems and Software, 2021 - Elsevier
Software defect prediction aims to identify the potential defects of new software modules in
advance by constructing an effective prediction model. However, the model performance is …

Performance analysis of feature selection methods in software defect prediction: a search method approach

AO Balogun, S Basri, SJ Abdulkadir, AS Hashim - applied sciences, 2019 - mdpi.com
Software Defect Prediction (SDP) models are built using software metrics derived from
software systems. The quality of SDP models depends largely on the quality of software …

The impact of feature reduction techniques on defect prediction models

M Kondo, CP Bezemer, Y Kamei, AE Hassan… - Empirical Software …, 2019 - Springer
Defect prediction is an important task for preserving software quality. Most prior work on
defect prediction uses software features, such as the number of lines of code, to predict …

A large-scale study of the impact of feature selection techniques on defect classification models

B Ghotra, S McIntosh, AE Hassan - 2017 IEEE/ACM 14th …, 2017 - ieeexplore.ieee.org
The performance of a defect classification model depends on the features that are used to
train it. Feature redundancy, correlation, and irrelevance can hinder the performance of a …

[HTML][HTML] Diabetic retinal fundus images: Preprocessing and feature extraction for early detection of diabetic retinopathy

DS Sisodia, S Nair… - Biomedical and …, 2017 - biomedpharmajournal.org
The investigation of clinical reports suggested that more than ten percent patients with
diabetes have a high risk of eye issues. Diabetic Retinopathy (DR) is an eye ailment which …

The impact of feature selection techniques on effort‐aware defect prediction: An empirical study

F Li, W Lu, JW Keung, X Yu, L Gong, J Li - IET Software, 2023 - Wiley Online Library
Abstract Effort‐Aware Defect Prediction (EADP) methods sort software modules based on
the defect density and guide the testing team to inspect the modules with high defect density …

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

SC Rathi, S Misra, R Colomo-Palacios… - Expert Systems with …, 2023 - Elsevier
Abstract Context: The application of Software Fault Prediction (SFP) in the software
development life cycle to predict the faulty class at the early stage has piqued the interest of …

Impact of feature selection methods on the predictive performance of software defect prediction models: an extensive empirical study

AO Balogun, S Basri, S Mahamad, SJ Abdulkadir… - Symmetry, 2020 - mdpi.com
Feature selection (FS) is a feasible solution for mitigating high dimensionality problem, and
many FS methods have been proposed in the context of software defect prediction (SDP) …

Empirical analysis of rank aggregation-based multi-filter feature selection methods in software defect prediction

AO Balogun, S Basri, S Mahamad, SJ Abdulkadir… - Electronics, 2021 - mdpi.com
Selecting the most suitable filter method that will produce a subset of features with the best
performance remains an open problem that is known as filter rank selection problem. A …