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.
Type
Publication
2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)
Anthony S. Peruma
Assistant Professor
My research interests include program comprehension and software refactoring.