Software fault prediction using deep learning algorithms
O Al Qasem, M Akour - … Journal of Open Source Software and …, 2019 - igi-global.com
Software faults prediction (SFP) processes can be used for detecting faulty constructs at
early stages of the development lifecycle, in addition to its being used in several phases of …
early stages of the development lifecycle, in addition to its being used in several phases of …
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 …
Software fault prediction using deep learning techniques
Software fault prediction (SFP) techniques identify faults at the early stages of the software
development life cycle (SDLC). We find machine learning techniques commonly used for …
development life cycle (SDLC). We find machine learning techniques commonly used for …
[HTML][HTML] Software fault prediction using an RNN-based deep learning approach and ensemble machine learning techniques
E Borandag - Applied Sciences, 2023 - mdpi.com
Alongside the modern software development life cycle approaches, software testing has
gained more importance and has become an area researched actively within the software …
gained more importance and has become an area researched actively within the software …
Predicting the Number of Software Faults using Deep Learning
W Alkaberi, F Assiri - Engineering, Technology & Applied Science …, 2024 - etasr.com
The software testing phase requires considerable time, effort, and cost, particularly when
there are many faults. Thus, developers focus on the evolution of Software Fault Prediction …
there are many faults. Thus, developers focus on the evolution of Software Fault Prediction …
A novel approach of software fault prediction using deep learning technique
Now-a-days, failure of the software is unavoidable due to increasing size and complexity of
software. So, fault finding is necessary for removing the software faults. Spectrum-based …
software. So, fault finding is necessary for removing the software faults. Spectrum-based …
Software defect prediction based on machine learning and deep learning
P Tadapaneni, NC Nadella, M Divyanjali… - 2022 International …, 2022 - ieeexplore.ieee.org
Software system quality can be enhanced by reducing the possible software defects in the
system, this can be achieved by regular monitoring of the system for any defect alerts …
system, this can be achieved by regular monitoring of the system for any defect alerts …
Software fault prediction using machine-learning techniques
Abstract Machine-learning techniques are used to find the defect, fault, ambiguity, and bad
smell to accomplish quality, maintainability, and reusability in software. Software fault …
smell to accomplish quality, maintainability, and reusability in software. Software fault …
Machine learning based methods for software fault prediction: A survey
SK Pandey, RB Mishra, AK Tripathi - Expert Systems with Applications, 2021 - Elsevier
Several prediction approaches are contained in the arena of software engineering such as
prediction of effort, security, quality, fault, cost, and re-usability. All these prediction …
prediction of effort, security, quality, fault, cost, and re-usability. All these prediction …
Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review
Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …
as modules or classes, early in the software development life cycle. There are data mining …