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 …

A literature review of using machine learning in software development life cycle stages

S Shafiq, A Mashkoor, C Mayr-Dorn, A Egyed - IEEE Access, 2021 - ieeexplore.ieee.org
The software engineering community is rapidly adopting machine learning for transitioning
modern-day software towards highly intelligent and self-learning systems. However, the …

A survey of aiops methods for failure management

P Notaro, J Cardoso, M Gerndt - ACM Transactions on Intelligent …, 2021 - dl.acm.org
Modern society is increasingly moving toward complex and distributed computing systems.
The increase in scale and complexity of these systems challenges O&M teams that perform …

Application of deep learning in software defect prediction: systematic literature review and meta-analysis

ZM Zain, S Sakri, NHA Ismail - Information and Software Technology, 2023 - Elsevier
Context Despite recent attention given to Software Defect Prediction (SDP), the lack of any
systematic effort to assess existing empirical evidence on the application of Deep Learning …

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 …

Empirical evaluation of the performance of data sampling and feature selection techniques for software fault prediction

SC Rathi, S Misra, R Colomo-Palacios… - Expert Systems with …, 2023 - Elsevier
Abstract Context: The application of Software Fault Prediction (SFP) in the software
development life cycle to predict the faulty class at the early stage has piqued the interest of …

[HTML][HTML] Industrial applications of software defect prediction using machine learning: A business-driven systematic literature review

S Stradowski, L Madeyski - Information and Software Technology, 2023 - Elsevier
Context: Machine learning software defect prediction is a promising field of software
engineering, attracting a great deal of attention from the research community; however, its …

Vulnerable code detection using software metrics and machine learning

N Medeiros, N Ivaki, P Costa, M Vieira - IEEE Access, 2020 - ieeexplore.ieee.org
Software metrics are widely-used indicators of software quality and several studies have
shown that such metrics can be used to estimate the presence of vulnerabilities in the code …

Software bug prediction using supervised machine learning algorithms

SD Immaculate, MF Begam… - … conference on data …, 2019 - ieeexplore.ieee.org
Machine Learning algorithms sprawl their application in various fields relentlessly. Software
Engineering is not exempted from that. Software bug prediction at the initial stages of …

Software defect prediction with Bayesian approaches

MJ Hernández-Molinos, AJ Sánchez-García… - Mathematics, 2023 - mdpi.com
Software defect prediction is an important area in software engineering because it helps
developers identify and fix problems before they become costly and hard-to-fix bugs. Early …