A comparative study to benchmark cross-project defect prediction approaches

S Herbold, A Trautsch, J Grabowski - Proceedings of the 40th …, 2018 - dl.acm.org
Cross-Project Defect Prediction (CPDP) as a means to focus quality assurance of software
projects was under heavy investigation in recent years. However, within the current state-of …

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

X Yang, D Lo, X Xia, 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 …

Cross-project defect prediction using a connectivity-based unsupervised classifier

F Zhang, Q Zheng, Y Zou, AE Hassan - Proceedings of the 38th …, 2016 - dl.acm.org
Defect prediction on projects with limited historical data has attracted great interest from both
researchers and practitioners. Cross-project defect prediction has been the main area of …

An empirical study of model-agnostic techniques for defect prediction models

J Jiarpakdee, CK Tantithamthavorn… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Software analytics have empowered software organisations to support a wide range of
improved decision-making and policy-making. However, such predictions made by software …

Software defect prediction based on kernel PCA and weighted extreme learning machine

Z Xu, J Liu, X Luo, Z Yang, Y Zhang, P Yuan… - Information and …, 2019 - Elsevier
Context Software defect prediction strives to detect defect-prone software modules by mining
the historical data. Effective prediction enables reasonable testing resource allocation …

An empirical study on software defect prediction with a simplified metric set

P He, B Li, X Liu, J Chen, Y Ma - Information and Software Technology, 2015 - Elsevier
Context Software defect prediction plays a crucial role in estimating the most defect-prone
components of software, and a large number of studies have pursued improving prediction …

Automatic feature learning for predicting vulnerable software components

HK Dam, T Tran, T Pham, SW Ng… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
Code flaws or vulnerabilities are prevalent in software systems and can potentially cause a
variety of problems including deadlock, hacking, information loss and system failure. A …

How far we have progressed in the journey? an examination of cross-project defect prediction

Y Zhou, Y Yang, H Lu, L Chen, Y Li, Y Zhao… - ACM Transactions on …, 2018 - dl.acm.org
Background. Recent years have seen an increasing interest in cross-project defect
prediction (CPDP), which aims to apply defect prediction models built on source projects to a …

Software defect prediction: do different classifiers find the same defects?

D Bowes, T Hall, J Petrić - Software Quality Journal, 2018 - Springer
During the last 10 years, hundreds of different defect prediction models have been
published. The performance of the classifiers used in these models is reported to be similar …

Bug localization with combination of deep learning and information retrieval

AN Lam, AT Nguyen, HA Nguyen… - 2017 IEEE/ACM 25th …, 2017 - ieeexplore.ieee.org
The automated task of locating the potential buggy files in a software project given a bug
report is called bug localization. Bug localization helps developers focus on crucial files …