| Full text | |
| Author(s): |
Gomes, Luiz
;
Torres, Ricardo da Silva
;
Cortes, Mario Lucio
Total Authors: 3
|
| Document type: | Journal article |
| Source: | INFORMATION AND SOFTWARE TECHNOLOGY; v. 160, p. 12-pg., 2023-04-20. |
| Abstract | |
Context: The correct prediction of long-lived bugs could help maintenance teams to build their plan and to fix more bugs that often adversely affect software quality and disturb the user experience across versions in Free/Libre Open-Source Software (FLOSS). Machine Learning and Text Mining methods have been applied to solve many real-world prediction problems, including bug report handling.Objective: Our research aims to compare the accuracy of ML classifiers on long-lived bug prediction in FLOSS using Bidirectional Encoder Representations from Transformers (BERT)-and Term Frequency -Inverse Document Frequency (TF-IDF)-based feature extraction. Besides that, we aim to investigate BERT variants on the same task.Method: We collected bug reports from six popular FLOSS and used the Machine Learning classifiers to predict long-lived bugs. Furthermore, we compare different feature extractors, based on BERT and TF-IDF methods, in long-lived bug prediction.Results: We found that long-lived bug prediction using BERT-based feature extraction systematically outper-formed the TF-IDF. The SVM and Random Forest outperformed other classifiers in almost all datasets using BERT. Furthermore, smaller BERT architectures show themselves as competitive.Conclusion: Our results demonstrated a promising avenue to predict long-lived bugs based on BERT contextual embedding features and fine-tuning procedures. (AU) | |
| FAPESP's process: | 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems |
| Grantee: | Leonor Patricia Cerdeira Morellato |
| Support Opportunities: | Research Program on Global Climate Change - University-Industry Cooperative Research (PITE) |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 16/50250-1 - The secret of playing football: Brazil versus the Netherlands |
| Grantee: | Sergio Augusto Cunha |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 15/24494-8 - Communications and processing of big data in cloud and fog computing |
| Grantee: | Nelson Luis Saldanha da Fonseca |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 14/50715-9 - Characterizing and predicting biomass production in sugarcane and eucalyptus plantations in Brazil |
| Grantee: | Rubens Augusto Camargo Lamparelli |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |
| FAPESP's process: | 17/20945-0 - Multi-user equipment approved in great 16/50250-1: local positioning system |
| Grantee: | Sergio Augusto Cunha |
| Support Opportunities: | Multi-user Equipment Program |