Software defect prediction using artificial neural networks: A systematic literature review

MA Khan, NS Elmitwally, S Abbas, S Aftab… - Scientific …, 2022 - Wiley Online Library
The demand for automated online software systems is increasing day by day, which
triggered the need for high‐quality and maintainable softwares at lower cost. Software defect …

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 …

[HTML][HTML] Software defect prediction based on nested-stacking and heterogeneous feature selection

L Chen, C Wang, S Song - Complex & Intelligent Systems, 2022 - Springer
Software testing guarantees the delivery of high-quality software products, and software
defect prediction (SDP) has become an important part of software testing. Software defect …

[HTML][HTML] Customer churning analysis using machine learning algorithms

B Prabadevi, R Shalini, BR Kavitha - International Journal of Intelligent …, 2023 - Elsevier
Businesses must compete fiercely to win over new consumers from suppliers. Since it
directly affects a company's revenue, client retention is a hot topic for analysis, and early …

[PDF][PDF] Software defect prediction using variant based ensemble learning and feature selection techniques.

U Ali, S Aftab, A Iqbal, Z Nawaz, MS Bashir… - International Journal of …, 2020 - mecs-press.org
Testing is considered as one of the expensive activities in software development process.
Fixing the defects during testing process can increase the cost as well as the completion …

[HTML][HTML] 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 …

SMOTE-based homogeneous ensemble methods for software defect prediction

AO Balogun, FB Lafenwa-Balogun, HA Mojeed… - … Science and Its …, 2020 - Springer
Class imbalance is a prevalent problem in machine learning which affects the prediction
performance of classification algorithms. Software Defect Prediction (SDP) is no exception to …

Generative oversampling methods for handling imbalanced data in software fault prediction

SS Rathore, SS Chouhan, DK Jain… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Imbalanced software fault datasets, having fewer faulty modules than the nonfaulty modules,
make accurate fault prediction difficult. It is challenging for software practitioners to handle …