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ALBFL: A novel neural ranking model for software fault localization via combining static and dynamic features

  • Published:2021-11 Issue: Volume:139 Page:106653
  • ISSN:0950-5849
  • Container-title:Information and Software Technology
  • language:en
  • Short-container-title:Information and Software Technology

Author:

Xiao Xi,Pan Yuqing,Zhang Bin,Hu Guangwu,Li Qing,Lu Runiu

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference31 articles.

1. Improving bug localization with word embedding and enhanced convolutional neural networks;Xiao;J. Inf. Softw. Technol.,2018

2. Shifting to mobile: network-based empirical study of mobile vulnerability market;Huang;IEEE Trans. Serv. Comput.,2016

3. FineLocator: a novel approach to method-level fine-grained bug localization by query expansion;Zhang;J. Inf. Softw. Technol.,2019

4. Using bug descriptions to reformulate queries during text-retrieval-based bug localization;Chaparro;J. Empiri. Softw. Eng.,2019

5. Network-clustered multi-modal bug localization;Hoang;IEEE Trans. Softw. Eng.,2019

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1. FCTree: Visualization of function calls in execution;Information and Software Technology;2024-11

2. Effective fault localization using probabilistic and grouping approach;International Journal of System Assurance Engineering and Management;2024-08-18

3. Software Fault Localization Based on Weighted Association Rule Mining and Complex Networks;Mathematics;2024-07-05

4. Combining Error Guessing and Logical Reasoning for Software Fault Localization via Deep Learning;International Journal of Software Engineering and Knowledge Engineering;2024-05-28

5. BOSS: A dataset to train ML-based systems to repair programs with out-of-bounds write flaws;Proceedings of the 5th ACM/IEEE International Workshop on Automated Program Repair;2024-04-20
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