A feature selection model for software defect prediction using binary Rao optimization algorithm

K Thirumoorthy - Applied Soft Computing, 2022 - Elsevier
In this digital world, using software has become an important part of daily life and business.
The software must be rigorously tested in order to avert a financial crisis. The defect-free …

Exploring the Intersection between Software Maintenance and Machine Learning—A Systematic Mapping Study

OA Bastías, J Díaz, J López Fenner - Applied Sciences, 2023 - mdpi.com
While some areas of software engineering knowledge present great advances with respect
to the automation of processes, tools, and practices, areas such as software maintenance …

A novel data-driven machine learning techniques to predict compressive strength of fly ash and recycled coarse aggregates based self-compacting concrete

S Aggarwal, R Singh, A Rathore, K Kapoor… - Materials Today …, 2024 - Elsevier
Compressive strength (CS) of concrete is one of the most important factors in the
construction industry and various time and effort-consuming tasks are required to measure it …

A clustering approach for software defect prediction using hybrid social mimic optimization algorithm

K Thirumoorthy, JJJ Britto - Computing, 2022 - Springer
In this information era, software usage is intertwined with daily routine work and business.
Defects in software can cause a severe economic crisis. It is a crucial task in the software …

Toward data-driven research: preliminary study to predict surface roughness in material extrusion using previously published data with machine learning

F García-Martínez, D Carou… - Rapid Prototyping …, 2023 - emerald.com
Purpose Material extrusion is one of the most commonly used approaches within the
additive manufacturing processes available. Despite its popularity and related technical …

A Cross-Project Defect Prediction Model Based on Deep Learning With Self-Attention

W Wen, R Zhang, C Wang, C Shen, M Yu… - IEEE …, 2022 - ieeexplore.ieee.org
Cross-project defect prediction technique is a hot topic in the field of software defect
research because of the huge difference in data distribution between source project and …

Software defect prediction: an ensemble learning approach

Z Yang, C Jin, Y Zhang, J Wang… - Journal of Physics …, 2022 - iopscience.iop.org
Software defect prediction plays an increasingly critical role in emerging software systems.
However, existing software defect prediction approaches typically suffer from low accuracy …

[HTML][HTML] Highlighting bugs in software development codes using SDPET for enhancing security

NA Bhaskaran, M Durairaj - Measurement: Sensors, 2023 - Elsevier
The requirement for high-quality, inexpensive software that can be maintained is being
driven by the rise in demand for automated online software systems. Early defect …

[PDF][PDF] Performance Analysis of Classification Algorithms for Software Defects Prediction by Mathematical Modelling & Simulations

SY Shaikh, NA Qureshi, MZ Khan… - Journal of Software …, 2023 - sjhse.smiu.edu.pk
This study explores machine learning (ML) techniques for Software defects prediction (SDP)
by using Mathematical Modelling & Simulation. The SDP is also used in the critical systems …

Critical Analysis of the Utilization of Machine Learning Techniques in the Context of Software Effort Estimation

C Pareta, R Mathur, AK Sharma - International Conference on Information …, 2023 - Springer
Software effort estimate is important today. All software development processes and
lifecycles require an important step in the process is software effort estimating (SEE) …