A Systematic Mapping of Bug Classification and Categorization Techniques in Software
DOI:
https://doi.org/10.5753/reic.2025.6850Keywords:
Bug classification, Bug categorization, Systematic mapping, SoftwareAbstract
This study is a systematic mapping of the literature on approaches to classifying and categorizing bugs in software, analyzing 33 final articles published between 2019 and 2024. The protocol was conducted following the PRISMA model, using the Parsifal tool for screening, and the search was performed in the ISI Web of Science, IEEE Xplore, Scopus, and Engineering Village databases. Data synthesis was performed through qualitative analysis and standardized extraction, focusing on technologies, data types, application contexts, and categorization criteria. The research revealed the predominance of supervised algorithms (such as Naive Bayes and Support Vector Machine) and the dependence on unstructured textual data from open-source repositories such as Mozilla and Eclipse. The exclusivity of open-source data restricts understanding of the bug life cycle in industrial contexts. Consequently, there is a need for future research exploring corporate environments and the integration of hybrid models (structured and unstructured data) to better reflect the bug life cycle.
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