Forming Software Development Team: Machine-Learning Approach
| dc.contributor.author | Tanbour, Zeina | |
| dc.contributor.author | Khudarieh, Doha | |
| dc.contributor.author | Abuodeh, Hadeel | |
| dc.date.accessioned | 2022-08-28T10:22:37Z | |
| dc.date.available | 2022-08-28T10:22:37Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Abstract—Software development team formation is a task done by skilled persons who have enough experience in mapping crew members to project tasks. Choosing software development team members according to their experience and within the amount of available budget/time is a vital task. However, the availability of a tool to suggest the best team members to the different tasks in some projects will definitely help project managers in their selections. This work is related to suggesting the most suitable skilled software development professionals to projects tasks based on some machine learning technique (Random Forest Classifier). The project manager just feeds the tool with the required tasks, and the latter suggests a ranked list of the most suitable professionals that fit each task which reflects positively on the team formation process. The experimental results conducted at the end of the work reflect the improvement of software development team formation gained comparable with the ordinary, self-experience-based one. Index Terms—Software Development, Machine Learning, Members Selection, Members-Tasks Mapping. | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.11888/17053 | |
| dc.language.iso | en | en_US |
| dc.title | Forming Software Development Team: Machine-Learning Approach | en_US |
| dc.type | Graduation project | en_US |
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