Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26020
Title: Fault-insertion and fault-fixing behavioural patterns in Apache Software Foundation Projects
Authors: Ortu, M
Destefanis, G
Hall, T
Bowes, D
Keywords: analysis;LDA;Mining software repositories
Issue Date: 24-Feb-2023
Publisher: Elsevier
Citation: Ortu, M. et al. (2023) 'Fault-insertion and fault-fixing behavioural patterns in Apache Software Foundation Projects', Information and Software Technology, 158, 107187, pp. 1 - 21. doi: 10.1016/j.infsof.2023.107187.
Abstract: Copyright © 2023 The Authors. Background: Developers inevitably make human errors while coding. These errors can lead to faults in code, some of which may result in system failures. It is important to reduce the faults inserted by developers as well as fix any that slip through. Aim: To investigate the fault insertion and fault fixing activities of developers. We identify developers who insert and fix faults, ask whether code topic ‘experts’ insert fewer faults, and experts fix more faults and whether patterns of insertion and fixing change over time. Methods: We perform a time-based analysis of developer activity on twelve Apache projects using Latent Dirichlet Allocation (LDA), Network Analysis and Topic Modelling. We also build three models (using Petri-net, Markov Chain and Hawkes Processes) which describe and simulate developers’ bug-introduction and fixing behaviour. Results: We show that: the majority of the projects we analysed have developers who dominate in the insertion and fixing of faults; Faults are less likely to be inserted by developers with code topic expertise; Different projects have different patterns of fault inserting and fixing over time. Conclusions: We recommend that projects identify the code topic expertise of developers and use expertise information to inform the assignment of project work.
Description: Data availability: Data are available [as described in the article].
URI: https://bura.brunel.ac.uk/handle/2438/26020
DOI: https://doi.org/10.1016/j.infsof.2023.107187
ISSN: 0950-5849
Other Identifiers: ORCID iD: Giuseppe Destefanis https://orcid.org/0000-0003-3982-6355.
107187
Appears in Collections:Dept of Computer Science Research Papers

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