Improved mayfly optimization deep stacked sparse auto encoder feature selection scorched gradient descent driven dropout XLM learning framework for software …

M Anbu - Concurrency and Computation: Practice and …, 2022 - Wiley Online Library
Software testing is the process of improving software quality by classifying and removing
defects in the software development. Previously, several methods were used for software …

Software defect prediction based on stacked sparse denoising autoencoders and enhanced extreme learning machine

N Zhang, S Ying, K Zhu, D Zhu - IET software, 2022 - Wiley Online Library
Software defect prediction is an important software quality assurance technique.
Nevertheless, the prediction performance of the constructed model is easily susceptible to …

A Novel Approach to Enhance Software Defect Prediction using An Improved Grey Wolf Optimization based Extreme Learning Machine Technique

S Mallik, D Pradhan, D Muduli, A Rath, G Panda… - 2024 - researchsquare.com
In software development and testing, detecting and mitigating faults are paramount to
prevent potential issues from escalating and disrupting the development and testing …

WSO-KELM: War Strategy Optimization-Based Kernel Extreme Learning Machine for Automatic Software Fault Prediction Model

JB Elci, S Nandagopalan - Journal of The Institution of Engineers (India) …, 2024 - Springer
The software development projects' testing part is usually expensive and complex, but it is
essential to gauge the effectiveness of the developed software. Software Fault Prediction …

Sdp-ml: an automated approach of software defect prediction employing machine learning techniques

MN Uddin, B Li, MN Mondol… - 2021 International …, 2021 - ieeexplore.ieee.org
Software Defect Prediction (SDP) method plays a vital role to ensure the software quality by
predicting bugs in software development phase. In addition, this technique also assists …

Cascade Generalization-based Classifiers for Software Defect Prediction

A Bashir, A Balogun, M Adigun, S Ajagbe… - arXiv preprint arXiv …, 2024 - arxiv.org
The process of software defect prediction (SDP) involves predicting which software system
modules or components pose the highest risk of being defective. The projections and …

[HTML][HTML] Attention based GRU-LSTM for software defect prediction

HS Munir, S Ren, M Mustafa, CN Siddique, S Qayyum - Plos one, 2021 - journals.plos.org
Software defect prediction (SDP) can be used to produce reliable, high-quality software. The
current SDP is practiced on program granular components (such as file level, class level, or …

Improved software defect prediction using Pruned Histogram-based isolation forest

Z Ding, L Xing - Reliability Engineering & System Safety, 2020 - Elsevier
Software defect prediction (SDP) is a hot topic in the modern software engineering research
community. It has been used for evaluating software quality and reliability and allocating …

Hybrid model with optimization tactics for software defect prediction

SG Gollagi, S Balasubramaniam - International Journal of Modeling …, 2023 - World Scientific
Defects are frequent in software systems, and they can cause a lot of issues for users.
Despite the fact that many studies have been conducted on employing software product …

Software defect prediction based on weighted extreme learning machine

J Gai, S Zheng, H Yu, H Yang - Multiagent and Grid Systems, 2020 - content.iospress.com
The uncertainty of developers' activity can lead to engineering problems such as increased
software defects during software development. Therefore, advanced approaches to …