Automated Support for Scrum Projects Sprint Planning
Abstract
In this paper an approach to support Sprint Planning in Scrum projects is discussed. This approach allows the automatic determination of the optimal set of tasks for a given sprint, as well as its execution flow, considering the a priori information concerning the current state of the project, tasks's difficulty and importance, and the relations between tasks. The proposed solution is based on the representation of the project decision space, defined by this information, as workflow models. To evaluate the approach, a prototype has been developed and is being assessed in the context of the Cornea Notification and Collecting Information System (Sincap) project. The results suggest that the use of the approach provides greater determinism for the sprint planning process, easies the viewing and evaluation of project scenarios and decreases planning time.
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Index Terms
- Automated Support for Scrum Projects Sprint Planning
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Sponsors
- Fundacao de Amparo a Pesquisa do Estado de Goias: FAPEG
- SBC: Brazilian Computer Society
- Institute of Informatics/Federal University of Goias: INF/UFG
- Faculdades ALFA: Faculdades ALFA
- Global RH Solutions: Global RH Solutions
- Secretaria de Ciencia, Tecnologia e Inovacao do Estado de Goias: SECTEC-GO
- CAPES: Brazilian Higher Education Funding Council
In-Cooperation
- SIGAPP: ACM Special Interest Group on Applied Computing
- SIGMIS: ACM Special Interest Group on Management Information Systems
- AIS: Assoc for Information Systems
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Brazilian Computer Society
Porto Alegre, Brazil
Publication History
Published: 26 May 2015
Accepted: 01 April 2015
Received: 01 February 2015
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- Research-article
- Research
- Refereed limited
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SBSI '15
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- Fundacao de Amparo a Pesquisa do Estado de Goias
- SBC
- Institute of Informatics/Federal University of Goias
- Faculdades ALFA
- Global RH Solutions
- Secretaria de Ciencia, Tecnologia e Inovacao do Estado de Goias
- CAPES
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SBSI '15 Paper Acceptance Rate 101 of 313 submissions, 32%;
Overall Acceptance Rate 181 of 557 submissions, 32%
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