TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formation
TeamPlus is a data-driven tool designed to optimize software team formation. By integrating with project management systems, it leverages data analytics to create detailed profiles and suggest optimal team configurations, allowing for managerial adjustments. We implemented this tool using a Genetic...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2025-05-01
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| Series: | SoftwareX |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711025001414 |
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| author | Felipe Cunha Mirko Perkusich Danyllo Albuquerque Kyller Gorgônio Hyggo Almeida Angelo Perkusich |
| author_facet | Felipe Cunha Mirko Perkusich Danyllo Albuquerque Kyller Gorgônio Hyggo Almeida Angelo Perkusich |
| author_sort | Felipe Cunha |
| collection | DOAJ |
| description | TeamPlus is a data-driven tool designed to optimize software team formation. By integrating with project management systems, it leverages data analytics to create detailed profiles and suggest optimal team configurations, allowing for managerial adjustments. We implemented this tool using a Genetic Algorithm (GA) with Convex Combination Crossover and validated it through two approaches: an experiment comparing our GA with traditional methods (i.e., Partially Mapped Crossover and One-Point Crossover) using data from 47 projects and 149 developers, and an evaluation of fifteen features by an industry expert, comparing them with tools from six recent studies. Our GA significantly outperformed traditional crossover methods, and TeamPlus offers a more comprehensive and flexible set of features, improving decision-making efficiency and team formation quality. |
| format | Article |
| id | doaj-art-6679734bb5f24b2e8e422c6818a8ab03 |
| institution | OA Journals |
| issn | 2352-7110 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj-art-6679734bb5f24b2e8e422c6818a8ab032025-08-20T02:30:18ZengElsevierSoftwareX2352-71102025-05-013010217410.1016/j.softx.2025.102174TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formationFelipe Cunha0Mirko Perkusich1Danyllo Albuquerque2Kyller Gorgônio3Hyggo Almeida4Angelo Perkusich5Research, Development and Innovation Center of Federal University of Campina Grande (VIRTUS/UFCG), Paraiba, BrazilResearch, Development and Innovation Center of Federal University of Campina Grande (VIRTUS/UFCG), Paraiba, BrazilCorresponding author.; Research, Development and Innovation Center of Federal University of Campina Grande (VIRTUS/UFCG), Paraiba, BrazilResearch, Development and Innovation Center of Federal University of Campina Grande (VIRTUS/UFCG), Paraiba, BrazilResearch, Development and Innovation Center of Federal University of Campina Grande (VIRTUS/UFCG), Paraiba, BrazilResearch, Development and Innovation Center of Federal University of Campina Grande (VIRTUS/UFCG), Paraiba, BrazilTeamPlus is a data-driven tool designed to optimize software team formation. By integrating with project management systems, it leverages data analytics to create detailed profiles and suggest optimal team configurations, allowing for managerial adjustments. We implemented this tool using a Genetic Algorithm (GA) with Convex Combination Crossover and validated it through two approaches: an experiment comparing our GA with traditional methods (i.e., Partially Mapped Crossover and One-Point Crossover) using data from 47 projects and 149 developers, and an evaluation of fifteen features by an industry expert, comparing them with tools from six recent studies. Our GA significantly outperformed traditional crossover methods, and TeamPlus offers a more comprehensive and flexible set of features, improving decision-making efficiency and team formation quality.http://www.sciencedirect.com/science/article/pii/S2352711025001414Software team formationIntelligent software engineeringGenetic algorithms |
| spellingShingle | Felipe Cunha Mirko Perkusich Danyllo Albuquerque Kyller Gorgônio Hyggo Almeida Angelo Perkusich TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formation SoftwareX Software team formation Intelligent software engineering Genetic algorithms |
| title | TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formation |
| title_full | TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formation |
| title_fullStr | TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formation |
| title_full_unstemmed | TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formation |
| title_short | TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formation |
| title_sort | teamplus a data driven tool utilizing a genetic algorithm for optimal software team formation |
| topic | Software team formation Intelligent software engineering Genetic algorithms |
| url | http://www.sciencedirect.com/science/article/pii/S2352711025001414 |
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