A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools

J Pachouly, S Ahirrao, K Kotecha… - … Applications of Artificial …, 2022 - Elsevier
Delivering high-quality software products is a challenging task. It needs proper coordination
from various teams in planning, execution, and testing. Many software products have high …

Empirical study of software defect prediction: a systematic map**

LH Son, N Pritam, M Khari, R Kumar, PTM Phuong… - Symmetry, 2019 - mdpi.com
Software defect prediction has been one of the key areas of exploration in the domain of
software quality. In this paper, we perform a systematic map** to analyze all the software …

TLEL: A two-layer ensemble learning approach for just-in-time defect prediction

X Yang, D Lo, X **a, J Sun - Information and Software Technology, 2017 - Elsevier
Context Defect prediction is a very meaningful topic, particularly at change-level. Change-
level defect prediction, which is also referred as just-in-time defect prediction, could not only …

A comparison of some soft computing methods for software fault prediction

E Erturk, EA Sezer - Expert systems with applications, 2015 - Elsevier
The main expectation from reliable software is the minimization of the number of failures that
occur when the program runs. Determining whether software modules are prone to fault is …

Empirical analysis of change metrics for software fault prediction

GR Choudhary, S Kumar, K Kumar, A Mishra… - Computers & Electrical …, 2018 - Elsevier
A quality assurance activity, known as software fault prediction, can reduce development
costs and improve software quality. The objective of this study is to investigate change …

Analysis and modeling conditional mutual dependency of metrics in software defect prediction using latent variables

NS Harzevili, SH Alizadeh - Neurocomputing, 2021 - Elsevier
Software defect prediction constitutes an important discipline in software development life-
cycle. Among the techniques employed in this domain, Naive Bayes (NB) classifier is cited …

Comparison of machine learning techniques for software quality prediction

S Goyal, PK Bhatia - … Journal of Knowledge and Systems Science …, 2020 - igi-global.com
Software quality prediction is one the most challenging tasks in the development and
maintenance of software. Machine learning (ML) is widely being incorporated for the …

Explaining mispredictions of machine learning models using rule induction

J Cito, I Dillig, S Kim, V Murali, S Chandra - … of the 29th ACM joint meeting …, 2021 - dl.acm.org
While machine learning (ML) models play an increasingly prevalent role in many software
engineering tasks, their prediction accuracy is often problematic. When these models do …

Iterative software fault prediction with a hybrid approach

E Erturk, EA Sezer - Applied Soft Computing, 2016 - Elsevier
In this study, we consider a software fault prediction task that can assist a developer during
the lifetime of a project. We aim to improve the performance of software fault prediction task …

Hyperparameter analysis of wide-kernel cnn architectures in industrial fault detection: an exploratory study

J Van Den Hoogen, D Hudson, S Bloemheuvel… - International Journal of …, 2024 - Springer
Industrial fault detection has become more data-driven due to advancements in automated
data analysis using deep learning. Such methods make it possible to extract useful features …