TeamPlus: A data-driven tool utilizing a Genetic Algorithm for optimal software team formation

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2025-05-01 DOI:10.1016/j.softx.2025.102174

Felipe Cunha, Mirko Perkusich, Danyllo Albuquerque, Kyller Gorgônio, Hyggo Almeida, Angelo Perkusich

引用次数: 0

Abstract

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.

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TeamPlus：一个数据驱动的工具，利用遗传算法来优化软件团队的形成

TeamPlus是一个数据驱动的工具，旨在优化软件团队的形成。通过与项目管理系统集成，它利用数据分析来创建详细的配置文件，并建议最佳的团队配置，允许管理调整。我们使用带有凸组合交叉的遗传算法（GA）实现了这个工具，并通过两种方法验证了它：使用来自47个项目和149个开发人员的数据将我们的遗传算法与传统方法（即部分映射交叉和单点交叉）进行比较的实验，以及由行业专家评估的15个特征，将它们与来自6个最近研究的工具进行比较。我们的遗传算法明显优于传统的交叉方法，TeamPlus提供了更全面、更灵活的功能，提高了决策效率和团队组建质量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.