Progress on approaches to software defect prediction
Software defect prediction is one of the most popular research topics in software
engineering. It aims to predict defect‐prone software modules before defects are discovered …
engineering. It aims to predict defect‐prone software modules before defects are discovered …
Data quality issues in software fault prediction: a systematic literature review
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 …
cost and time. Various machine learning models have been proposed in the past for …
Assessing countries' performances against COVID-19 via WSIDEA and machine learning algorithms
N Aydin, G Yurdakul - Applied Soft Computing, 2020 - Elsevier
The COVID-19 pandemic, which first spread to the People of Republic of China and then to
other countries in a short time, affected the whole world by infecting millions of people and …
other countries in a short time, affected the whole world by infecting millions of people and …
The impact of feature selection on defect prediction performance: An empirical comparison
Software defect prediction aims to determine whether a software module is defect-prone by
constructing prediction models. The performance of such models is susceptible to the high …
constructing prediction models. The performance of such models is susceptible to the high …
Improving defect prediction with deep forest
Context Software defect prediction is important to ensure the quality of software. Nowadays,
many supervised learning techniques have been applied to identify defective instances (eg …
many supervised learning techniques have been applied to identify defective instances (eg …
An empirical study on pareto based multi-objective feature selection for software defect prediction
The performance of software defect prediction (SDP) models depend on the quality of
considered software features. Redundant features and irrelevant features may reduce the …
considered software features. Redundant features and irrelevant features may reduce the …
Software defect prediction techniques using metrics based on neural network classifier
R Jayanthi, L Florence - Cluster Computing, 2019 - Springer
Software industries strive for software quality improvement by consistent bug prediction, bug
removal and prediction of fault-prone module. This area has attracted researchers due to its …
removal and prediction of fault-prone module. This area has attracted researchers due to its …
Software defect prediction using machine learning techniques
CL Prabha, N Shivakumar - 2020 4th International Conference …, 2020 - ieeexplore.ieee.org
Software defect prediction provides development groups with observable outcomes while
contributing to industrial results and development faults predicting defective code areas can …
contributing to industrial results and development faults predicting defective code areas can …
Cross project defect prediction via balanced distribution adaptation based transfer learning
Defect prediction assists the rational allocation of testing resources by detecting the
potentially defective software modules before releasing products. When a project has no …
potentially defective software modules before releasing products. When a project has no …
A comprehensive comparative study of clustering-based unsupervised defect prediction models
Software defect prediction recommends the most defect-prone software modules for
optimization of the test resource allocation. The limitation of the extensively-studied …
optimization of the test resource allocation. The limitation of the extensively-studied …