A fuzzy linguistic approach for human resource evaluation and selection in software projects

One of the key challenges in software projects is the efficient allocation of human resources to software development tasks. To achieve this challenge, the proper human resource evaluation and selection is an important step. In this paper we present a fuzzy linguistic approach that utilizes 2-tuple fuzzy linguistic terms and supports the selection of suitable human resources based on their skills and the required skills for each project task. The proposed approach follows a group, multi-criteria, similarity degree-based aggregation algorithm and results in an objective aggregation of the ratings of required task related skills and provided skills from candidate human resources. In addition, we consider skill relationships as 2-tuple fuzzy linguistic terms to reflect the contribution of one skill to the learning of other skills. The proposed approach has been implemented in the context of SPRINT SMEs project. SPRINT SMEs aims to suggest a practical framework of methods for the improvement of software processes which take place in small & medium sized software development enterprises.