Abstract
OCR engines aim to identify and extract text strings fromdocuments or images. While current efforts focus mostly inmainstream languages, there is little support for program-ming or domain-specific languages (DSLs). In this paper, wepresent our vision about the current state of OCR recognitionfor DSLs and its challenges. We discuss some strategies toimprove the OCR quality applied to DSL textual expressionsby leveraging DSL specifications and domain data. To bettersupport our ideas we present the preliminary results of anempirical study and outline a research roadmap.
Type
Publication
SLE 2020 - Proceedings of the 13th ACM SIGPLAN International Conference on Software Language Engineering, Co-located with SPLASH 2020
Roberto Rodriguez-Echeverria
Associate Professor
Associate Professor at Universidad de Extremadura. My research interests include Software Engineering, Model-Driven Engineering, Data Science, Machine Learning.