A novel approach to improve software defect prediction accuracy using machine learning
In software engineering community, defect prediction is one the active domain. For the
software's success, it is essential to reduce the software engineering and data-mining gap …
software's success, it is essential to reduce the software engineering and data-mining gap …
Analysis of feature selection methods in software defect prediction models
Improving software quality by proactively detecting potential defects during development is a
major goal of software engineering. Software defect prediction plays a central role in …
major goal of software engineering. Software defect prediction plays a central role in …
On the relative value of clustering techniques for unsupervised effort-aware defect prediction
P Yang, L Zhu, Y Zhang, C Ma, L Liu, X Yu… - Expert Systems with …, 2024 - Elsevier
Abstract Unsupervised Effort-Aware Defect Prediction (EADP) uses unlabeled data to
construct a model and ranks software modules according to the software feature values. Xu …
construct a model and ranks software modules according to the software feature values. Xu …
Noise-Aware Quantum Software Testing
Quantum Computing (QC) promises computational speedup over classic computing for
solving some complex problems. However, noise exists in current and near-term quantum …
solving some complex problems. However, noise exists in current and near-term quantum …
A two-stage stacked-based heterogeneous ensemble learning for cancer survival prediction
F Yan, Y Feng - Complex & Intelligent Systems, 2022 - Springer
Cancer survival prediction is one of the three major tasks of cancer prognosis. To improve
the accuracy of cancer survival prediction, in this paper, we propose a priori knowledge-and …
the accuracy of cancer survival prediction, in this paper, we propose a priori knowledge-and …
Machine learning-based defect prediction model using multilayer perceptron algorithm for escalating the reliability of the software
When it comes to software development, precise planning, proper documentation and
proper process control, some errors are inevitable in the software environment. These …
proper process control, some errors are inevitable in the software environment. These …
Enhancing IOT based software defect prediction in analytical data management using war strategy optimization and Kernel ELM
The existence of software problems in IoT applications caused by insufficient source code,
poor design, mistakes, and insufficient testing poses a serious risk to functioning and user …
poor design, mistakes, and insufficient testing poses a serious risk to functioning and user …
A tent lévy flying sparrow search algorithm for wrapper-based feature selection: A COVID-19 case study
The “Curse of Dimensionality” induced by the rapid development of information science
might have a negative impact when dealing with big datasets, and it also makes the …
might have a negative impact when dealing with big datasets, and it also makes the …
Ensemble Classifiers in Software Defect Prediction: A Systematic Literature Review
JA Olivares-Galindo, ÁJ Sánchez-García… - 2023 11th …, 2023 - ieeexplore.ieee.org
The Software Defect Prediction area is important in software development since it allows
anticipating possible software defects before they occur in production and affect end users. If …
anticipating possible software defects before they occur in production and affect end users. If …
Explainable prediction of daily hospitalizations for cerebrovascular disease using stacked ensemble learning
X Lu, H Qiu - BMC Medical Informatics and Decision Making, 2023 - Springer
Background With the prevalence of cerebrovascular disease (CD) and the increasing strain
on healthcare resources, forecasting the healthcare demands of cerebrovascular patients …
on healthcare resources, forecasting the healthcare demands of cerebrovascular patients …