A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools

J Pachouly, S Ahirrao, K Kotecha… - … Applications of Artificial …, 2022 - Elsevier
Delivering high-quality software products is a challenging task. It needs proper coordination
from various teams in planning, execution, and testing. Many software products have high …

COVID-19 detection from CBC using machine learning techniques

A Akhtar, S Akhtar, B Bakhtawar… - International Journal …, 2021 - journals.gaftim.com
Covid-19 pandemic has seriously affected the mankind with colossal loss of life around the
world. There is a critical requirement for timely and reliable detection of Corona virus …

Treatment response prediction in hepatitis C patients using machine learning techniques

AA Kashif, B Bakhtawar, A Akhtar… - International Journal …, 2021 - journals.gaftim.com
The proper prognosis of treatment response is crucial in any medical therapy to reduce the
effects of the disease and of the medication as well. The mortality rate due to hepatitis c virus …

The impact of using biased performance metrics on software defect prediction research

J Yao, M Shepperd - Information and Software Technology, 2021 - Elsevier
Context: Software engineering researchers have undertaken many experiments
investigating the potential of software defect prediction algorithms. Unfortunately some …

Improving performance with hybrid feature selection and ensemble machine learning techniques for code smell detection

S Jain, A Saha - Science of Computer Programming, 2021 - Elsevier
Maintaining large and complex software is a significant task in IT industry. One reason for
that is the development of code smells which are design flaws that lead to future bugs and …

Human-machine collaboration for feature selection and integration to improve congestive Heart failure risk prediction

O Ben-Assuli, T Heart, R Klempfner, R Padman - Decision support systems, 2023 - Elsevier
The issue of harnessing machine learning (ML) algorithms for the prediction of adverse
medical events is important considering the prevalence of vast repositories of patient-level …

Role of Feature Selection in Cross Project Software Defect Prediction-A Review

MS Saeed - International Journal of Computations, Information …, 2023 - journals.gaftim.com
Software Defect Prediction (SDP) is crucial for enhancing software quality and minimizing
issues after release. The advent of machine learning, particularly in Cross-Project Defect …

[HTML][HTML] A cloud-based software defect prediction system using data and decision-level machine learning fusion

S Aftab, S Abbas, TM Ghazal, M Ahmad, HA Hamadi… - Mathematics, 2023 - mdpi.com
This research contributes an intelligent cloud-based software defect prediction system using
data and decision-level machine learning fusion techniques. The proposed system detects …

[HTML][HTML] Reliable prediction of software defects using Shapley interpretable machine learning models

Y Al-Smadi, M Eshtay, A Al-Qerem, S Nashwan… - Egyptian Informatics …, 2023 - Elsevier
Predicting defect-prone software components can play a significant role in allocating
relevant testing resources to fault-prone modules and hence increasing the business value …

[HTML][HTML] Enhancing software defect prediction: a framework with improved feature selection and ensemble machine learning

M Ali, T Mazhar, A Al-Rasheed, T Shahzad… - PeerJ Computer …, 2024 - peerj.com
Effective software defect prediction is a crucial aspect of software quality assurance,
enabling the identification of defective modules before the testing phase. This study aims to …