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Accurate assessment of the domain expertise of developers is essential for assigning the proper candidate to contribute to a project, or to attend a job role. Since the potential candidate can come from a large pool, the automated assessment of this domain expertise is a desirable goal. While previous methods have had some success within a single software project, the assessment of a developer’s domain expertise from contributions across multiple projects is more challenging.

In this paper, we employ doc2vec to represent the domain expertise of developers across multiple projects as embedding vectors, and assess expertise level from authored code fragments.

For this purpose, we derived embedding vectors from different sources that contain evidence of developers’ expertise, such as the description of repositories they contributed, their issue resolving history, and API calls in their …