Investigating the use of deep neural networks for software defect prediction
M Samir, M El-Ramly, A Kamel - 2019 IEEE/ACS 16th …, 2019 - ieeexplore.ieee.org
Many software projects are shipped to customers containing defects. Defective software cost
money, time, and lives. To reduce this harm, software companies allocate testing and quality …
money, time, and lives. To reduce this harm, software companies allocate testing and quality …
Comparative Analysis of Machine Learning Technique to Improve Software Defect Prediction: Comparative Analysis of Machine Learning Technique to Improve …
One of the most active areas of research in the software engineering community is defect
prediction. The gap between data mining and software engineering must be bridged to …
prediction. The gap between data mining and software engineering must be bridged to …
A novel modified undersampling (MUS) technique for software defect prediction
P Lingden, A Alsadoon, PWC Prasad… - Computational …, 2019 - Wiley Online Library
Background and aim: Many sophisticated data mining and machine learning algorithms
have been used for software defect prediction (SDP) to enhance the quality of software …
have been used for software defect prediction (SDP) to enhance the quality of software …
The influence of deep learning algorithms factors in software fault prediction
The discovery of software faults at early stages plays an important role in improving software
quality; reduce the costs, time, and effort that should be spent on software development …
quality; reduce the costs, time, and effort that should be spent on software development …
Cognitive Complexity and Graph Convolutional Approach Over Control Flow Graph for Software Defect Prediction
The software engineering community is working to develop reliable metrics to improve
software quality. It is estimated that understanding the source code accounts for 60% of the …
software quality. It is estimated that understanding the source code accounts for 60% of the …
[PDF][PDF] A systematic literature review of software defect prediction
RS Wahono - Journal of software engineering, 2015 - romisatriawahono.net
Recent studies of software defect prediction typically produce datasets, methods and
frameworks which allow software engineers to focus on development activities in terms of …
frameworks which allow software engineers to focus on development activities in terms of …
Research of software defect prediction model based on complex network and graph neural network
M Cui, S Long, Y Jiang, X Na - Entropy, 2022 - mdpi.com
The goal of software defect prediction is to make predictions by mining the historical data
using models. Current software defect prediction models mainly focus on the code features …
using models. Current software defect prediction models mainly focus on the code features …
Improved prediction of software defects using ensemble machine learning techniques
S Mehta, KS Patnaik - Neural Computing and Applications, 2021 - Springer
Software testing process is a crucial part in software development. Generally the errors
made by developers get fixed at a later stage of the software development process. This …
made by developers get fixed at a later stage of the software development process. This …
Software defect prediction based on deep learning models: Performance study
In recent years, defect prediction, one of the major software engineering problems, has been
in the focus of researchers since it has a pivotal role in estimating software errors and faulty …
in the focus of researchers since it has a pivotal role in estimating software errors and faulty …
Machine learning-based software defect prediction for mobile applications: A systematic literature review
Software defect prediction studies aim to predict defect-prone components before the testing
stage of the software development process. The main benefit of these prediction models is …
stage of the software development process. The main benefit of these prediction models is …