Beyond Subjectiviness: Assessing Abilities and Preferences to Create Software Development Teams

Abstract

The creation of software development teams that are affected by performance issues is a problem frequently observed in companies in the software development market. This process is commonly done through subjective methodologies. Such methodologies can be influenced by interpersonal relationships and susceptible to human error. This paper proposes a quantitative and data-oriented alternative to the process of forming workgroups through the use of a genetic algorithm capable of optimizing collaborator’s abilities and preferences when executing a specific task within a project. As a result, we show that the use of such genetic algorithm is able to create teams similar to the teams assembled by the project managers of companies in the industry of software engineering. Therefore, the ability of genetic algorithm on supporting the process of develoment teams assembly becomes evident.