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Knowledge discovery in software teams by means of evolutionary visual software analytics

机译:通过进化的可视化软件分析,在软件团队中发现知识

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The day-to-day management of human resources that occurs during the development and maintenance process of software systems is a responsibility of project leads and managers, who usually perform such a task empirically. Moreover, rotation and distributed software development affect the establishment of long-term relationships between project managers and software projects, as well as between project managers and companies. It is also common for project leads and managers to face decision-making on human resources without the necessary prior knowledge. In this context, the application of visual analytics to software evolution supports software project leads and managers using analysis methods and a shared knowledge space for decision-making by means of visualization and interaction techniques. This approach offers the possibility of determining which programmer has led a project or contributed more to the development and maintenance of a software system in terms of revisions. Moreover, this approach helps to elucidate both the software items1 that have been changed in common by a group of programmers and who has changed what software items. With this information, software project leads and managers can make decisions regarding task assignment to developers and staff substitutions due to unexpected situations or staff turnover. Consequently, this research is aimed at supporting software practitioners in tasks related to human resources management through the application of Visual Analytics to Software Evolution.
机译:在软件系统的开发和维护过程中进行的日常人力资源管理是项目负责人和经理的责任,他们通常凭经验执行此类任务。此外,轮换和分布式软件开发会影响项目经理与软件项目之间以及项目经理与公司之间的长期关系。对于项目主管和经理来说,在没有必要的先验知识的情况下面对人力资源决策也很常见。在这种情况下,将可视化分析应用于软件演化可通过分析方法和共享的知识空间,通过可视化和交互技术,为软件项目负责人和管理人员提供决策支持。这种方法提供了一种可能性,即可以根据修订确定哪个程序员领导了一个项目或对软件系统的开发和维护做出了更多贡献。此外,这种方法有助于阐明一组程序员共同更改的软件项目1,以及谁更改了哪些软件项目。借助这些信息,软件项目负责人和管理人员可以针对由于意外情况或人员流动而导致的任务分配给开发人员和人员替换做出决策。因此,本研究旨在通过将可视化分析应用于软件演进来支持软件从业人员从事与人力资源管理相关的任务。

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