GitLab-EffortMiner: A framework for data extraction from DevOps environments for effort estimation
DOI:
https://doi.org/10.36825/RITI.14.35.002Keywords:
Agile, Effort Estimation, User Stories, Software Engineering, RepositoryAbstract
Effort estimation in software projects is a fundamental planning activity that can be affected by the lack of historical data and level of experience of the teams. This article presents a preliminary study on the development of a framework for extracting information from software repositories, aimed at effort estimation in agile software development projects. The framework consists of processes for mining, transforming, and adapting information to adjust the complexity of story points in accordance with the Generalized Estimation Method. The usefulness of the data obtained through the framework was validated using regression models for estimating adjusted story points, built with data extracted from 33 open-source projects from the User Story NeoDataset. The experimental results indicate that the information obtained through the framework is useful for estimating effort.
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