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DC Field | Value | Language |
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dc.contributor.author | Bowes, D | - |
dc.contributor.author | Destefanis, G | - |
dc.contributor.author | Hall, T | - |
dc.contributor.author | Petric, J | - |
dc.contributor.author | Ortu, M | - |
dc.coverage.spatial | Virtual, USA | - |
dc.date.accessioned | 2024-10-07T08:46:34Z | - |
dc.date.available | 2024-10-07T08:46:34Z | - |
dc.date.issued | 2020-11-08 | - |
dc.identifier | ORCiD: Giuseppe Destefanis https://orcid.org/0000-0003-3982-6355 | - |
dc.identifier.citation | Bowes, D. et al. (2020) 'Fault-insertion and fault-fixing: Analysing developer activity over time', PROMISE 2020: Proceedings of the 16th ACM International Conference on Predictive Models and Data Analytics in Software Engineering, 8-9 November, Virtual, pp. 41 - 50. doi: 10.1145/3416508.3417117. | en_US |
dc.identifier.isbn | 978-1-4503-8127-7 (ebk) | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/29895 | - |
dc.description.abstract | 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. 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. We perform a time-based analysis of developer activity on six Apache projects using Latent Dirichlet Allocation (LDA), Network Analysis and Topic Modelling. 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. We recommend that projects identify the code topic expertise of developers and use expertise information to inform the assignment of project work. We propose a preliminary analytics dashboard of data to enable projects to track fault insertion and fixing over time. This dashboard should help projects to identify any anomalous insertion and fixing activity. | en_US |
dc.description.sponsorship | This work is partly funded by grants from the UK’s Engineer-ing and Physical Sciences Research Council (EP/S005730/1 and EP/S005749/2). | en_US |
dc.format.extent | 41 - 50 | - |
dc.format.medium | Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Association for Computing Machinery (ACM) | en_US |
dc.rights | Copyright © 2020 Association for Computing Machinery. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in PROMISE '20: 16th International Conference on Predictive Models and Data Analytics in Software Engineering, https://doi.org/10.1145/3416508.3417117 (see: https://www.acm.org/publications/policies/publication-rights-and-licensing-policy). | - |
dc.rights.uri | https://www.acm.org/publications/policies/publication-rights-and-licensing-policy | - |
dc.source | PROMISE '20: 16th International Conference on Predictive Models and Data Analytics in Software Engineering | - |
dc.source | PROMISE '20: 16th International Conference on Predictive Models and Data Analytics in Software Engineering | - |
dc.subject | mining software repositories | en_US |
dc.subject | faults fixing | en_US |
dc.subject | networks | en_US |
dc.subject | software development | en_US |
dc.title | Fault-insertion and fault-fixing: Analysing developer activity over time | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | https://doi.org/10.1145/3416508.3417117 | - |
dc.relation.isPartOf | PROMISE 2020: Proceedings of the 16th ACM International Conference on Predictive Models and Data Analytics in Software Engineering | - |
pubs.finish-date | 2020-11-09 | - |
pubs.finish-date | 2020-11-09 | - |
pubs.publication-status | Published | - |
pubs.start-date | 2020-11-08 | - |
pubs.start-date | 2020-11-08 | - |
dc.rights.holder | Association for Computing Machinery (ACM) | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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File | Description | Size | Format | |
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FullText.pdf | Copyright © 2020 Association for Computing Machinery. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in PROMISE '20: 16th International Conference on Predictive Models and Data Analytics in Software Engineering, https://doi.org/10.1145/3416508.3417117 (see: https://www.acm.org/publications/policies/publication-rights-and-licensing-policy). | 2.48 MB | Adobe PDF | View/Open |
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