ST-TLF: Cross-version defect prediction framework based transfer learning

Y Zhao, Y Wang, Y Zhang, D Zhang, Y Gong… - Information and Software …, 2022 - Elsevier
Context: Cross-version defect prediction (CVDP) is a practical scenario in which defect
prediction models are derived from defect data of historical versions to predict potential …

Inter-release defect prediction with feature selection using temporal chunk-based learning: An empirical study

MA Kabir, J Keung, B Turhan, KE Bennin - Applied Soft Computing, 2021 - Elsevier
Inter-release defect prediction (IRDP) is a practical scenario that employs the datasets of the
previous release to build a prediction model and predicts defects for the current release …

CODE: A Moving-Window-Based Framework for Detecting Concept Drift in Software Defect Prediction

MA Kabir, S Begum, MU Ahmed, AU Rehman - Symmetry, 2022 - mdpi.com
Concept drift (CD) refers to data distributions that may vary after a minimum stable period.
CD negatively influences models' performance of software defect prediction (SDP) trained …

Evolutionary measures for object-oriented projects and impact on the performance of cross-version defect prediction

Q Yu, Y Zhu, H Han, Y Zhao, S Jiang… - Proceedings of the 13th …, 2022 - dl.acm.org
Cross-version defect prediction (CVDP) has attracted more attention of researchers in recent
years. For an evolutionary project, multiple versions will be produced during the process of …

Evolutionary measures and their correlations with the performance of cross‐version defect prediction for object‐oriented projects

Q Yu, Y Zhu, H Han, Y Zhao, S Jiang… - Journal of Software …, 2024 - Wiley Online Library
Cross‐version defect prediction (CVDP) for evolutionary projects has attracted much
attention from researchers in recent years. For multiple versions of an object‐oriented …

Effective Prediction of Software Defects using Random-tree Entropy based Feature Selection Framework

A Alhumam - … Journal of Advanced Computer Science and …, 2022 - search.proquest.com
Software systems have grown in size and complexity. These characteristics increase the
difficulty of preventing software errors. As a result, forecasting the frequency of software …

Toward a consistent performance evaluation for defect prediction models

X Liu, S Liu, Z Guo, P Zhag, Y Yang, H Liu, H Lu… - arXiv preprint arXiv …, 2023 - arxiv.org
In defect prediction community, many defect prediction models have been proposed and
indeed more new models are continuously being developed. However, there is no …

Interpretation Conclusion Stability of Software Defect Prediction over Time

A Nikanjam - 2024 - researchsquare.com
Abstract Model instability refers to where a machine learning model trained on historical
data becomes less reliable over time due to Concept Drift (CD). CD refers to the …