A Versatile Dataset of Agile Open Source Software Projects
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Abstract (arXiv)
Agile software development is nowadays a widely adopted practise in both open-source and industrial software projects. Agile teams typically heavily rely on issue management tools to document new issues and keep track of outstanding ones, in addition to storing their technical details, effort estimates, assignment to developers, and more. Previous work utilised the historical information stored in issue management systems for various purposes; however, when researchers make their empirical data public, it is usually relevant solely to the study's objective. In this paper, we present a more holistic and versatile dataset containing a wealth of information on more than 500,000 issues from 44 open-source Agile software, making it well-suited to several research avenues, and cross-analyses therein, including effort estimation, issue prioritization, issue assignment and many more. We make this data publicly available on GitHub to facilitate ease of use, maintenance, and extensibility.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Feb 2022.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 2.
4 papers.
- 2024Search-based Optimisation of LLM Learning Shots for Story Point Estimationcited by 5
- 2022Heterogeneous Graph Neural Networks for Software Effort Estimationcited by 3
- 2024User Story Tutor (UST) to Support Agile Software Developerscited by 2
- 2023Recent Advances in Software Effort Estimation using Machine Learningcited by 0
- 2024User Story Tutor (UST) to Support Agile Software Developers24 Jun 2024
- 2024Search-based Optimisation of LLM Learning Shots for Story Point Estimation13 Mar 2024
- 2023Recent Advances in Software Effort Estimation using Machine Learning6 Mar 2023
- 2022Heterogeneous Graph Neural Networks for Software Effort Estimation22 Jun 2022