Abstract
This paper presents the features of a model that relates the natural language found in identifiers with program semantics. The model takes advantage of part of speech information and static-analysis-based program models to understand how different types of statically-derived semantics correlates with the natural language meaning of identifiers.
This study has been accepted for publication at The International Conference on Software Maintenance and Evolution (ICSME 2019)