Analysis on user story backlog by text grouping and semantic similarity technique
Scrum is an agile methodology to manage and plan software projects. The product backlog is a Scrum gadget, consisting of a prioritized list of functionality, usually described as a user story. The amount of this user stories in a backlog is related to the size of the system to be developed, and in l...
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| Main Authors: | , , |
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| Format: | Online |
| Language: | Portuguese |
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Universidade Estadual de Campinas (UNICAMP)
2016
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| Subjects: | |
| Online Access: | https://econtents.sbu.unicamp.br/eventos/index.php/simtec/article/view/9163 |
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| Summary: | Scrum is an agile methodology to manage and plan software projects. The product backlog is a Scrum gadget, consisting of a prioritized list of functionality, usually described as a user story. The amount of this user stories in a backlog is related to the size of the system to be developed, and in large-scale systems, they can be massive. Although user stories are short texts, the large number of stories makes difficult the identification of existing relations between them, and brings additional effort to plan sprints, detect duplicated stories and identify stories that will suffer changes when including new requirements. This work's goal was to develop and apply an approach to analyze user stories through the text grouping and semantic similarity analysis technique. This approach will enable to support Scrum tasks, such as the product backlog refining and sprint planning. The results indicate that the use of a semantic similarity metric, in order to analyze short texts, is a promising approach to find existing relations between user stories. It is concluded that the use of this approach contributes to find duplicated user stories and stories that will evolve, in addition to contribute to obtain useful information that enable to improve the software development process. |
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| ISSN: | 2525-5398 |
