Distributed development is a constant need in the software industry. The allocation of tasks, in turn, is a critical activity for any project, especially in a distributed setting. Assigning a task to an individual or team can be done in a rigorous manner, taking into account a number of factors. In this scenario, the more data on factors that influence task assignment are available to support the assignment decision, the more likely the project will succeed. As a result, companies have been looking to build their big data with historical project data, aiming to better their chances of success. Some studies about task allocation in distributed software development (DSD) have been carried out along the years aiming at mapping this topic and its features. Also, some approaches, models, and frameworks to task allocation in DSD have been proposed. This paper presents a systematic review of the literature whose objective is to identify works based on multicriteria models for assigning tasks in DDS projects, especially those based on qualitative decision-making methods, considering the cognitive validity present in some of these methods. The review results allowed identifying several interesting aspects and classifying the works according to a set of questions. In addition, it has made some important findings that may be very useful for those who intend to conduct research with qualitative multicriteria methods, since some of them employ techniques considered psychologically valid to address the complexity of the decision about the task allocation in distributed projects.
Aiming to identify the related works to the present research, we have developed a systematic review of the literature, which is described in detail in REF .
Task Allocation in Distributed Software Development: A Systematic Literature Review
Complexity
Complexity
Mathematics Computer Science