Knowledge Classification for Supporting Effort Estimation in Global Software Engineering Projects

Abstract: Background: Global Software Engineering (GSE) has become a widely applied operational model for the development of software systems; it can increase profits and decrease time-to-market. However, there are many challenges associated with development of software in a globally distributed fashion. There is evidence that these challenges affect many process related to software development, such as effort estimation. To the best of our knowledge, there are no empirical studies to gather evidence on effort estimation in the GSE context. In addition, there is no common terminology for classifying GSE scenarios focusing on effort estimation.Objective: The main objective of this thesis is to support effort estimation in the GSE context by providing a taxonomy to classify the existing knowledge in this field.Method: Systematic literature review (to identify and analyze the state of the art), survey (to identify and analyze the state of the practice), systematic mapping (to identify practices to design software engineering taxonomies), and literature survey (to complement the states of the art and practice) were the methods employed in this thesis.Results: The results on the states of the art and practice show that the effort estimation techniques employed in the GSE context are the same techniques used in the collocated context. It was also identified that global aspects, e.g. time, geographical and social-cultural distances, are accounted for as cost drivers, although it is not clear how they are measured. As a result of the conducted mapping study, we reported a method that can be used to design new SE taxonomies. The aforementioned results were combined to extend and specialize an existing GSE taxonomy, for suitability for effort estimation. The usage of the specialized GSE effort estimation taxonomy was illustrated by classifying 8 finished GSE projects. The results show that the specialized taxonomy proposed in this thesis is comprehensive enough to classify GSE projects focusing on effort estimation.Conclusions: The taxonomy presented in this thesis will help researchers and practitioners to report new research on effort estimation in the GSE context; researchers and practitioners will be able to gather evidence, com- pare new studies and find new gaps in an easier way. The findings from this thesis show that more research must be conducted on effort estimation in the GSE context. For example, the way the cost drivers are measured should be further investigated. It is also necessary to conduct further research to clarify the role and impact of sourcing strategies on the effort estimates’ accuracies. Finally, we believe that it is possible to design an instrument based on the specialized GSE effort estimation taxonomy that helps practitioners to perform the effort estimation process in a way tailored for the specific needs of the GSE context.