Source Code Generation (SCG) is the sub-domain of the Automatic Programming (AP) that helps programmers to program using high-level abstraction. Recently, many researchers investigated many techniques to access SCG. The problem is to use the appropriate technique to generate the source code due to its purposes and the inputs. This paper introduces a review and an analysis related SCG techniques. Moreover, comparisons are presented for: techniques mapping, Natural Language Processing (NLP), knowledge base, ontology, Specification Configuration Template (SCT) model and deep learning
aloklah, anas hamid; gad, walaa; aref, mostafa mohamed prof; and salem, abd el-badea Mohamed prof
"Ontological Engineering For Source Code Generation,"
Future Computing and Informatics Journal: Vol. 4
, Article 1.
Available at: https://digitalcommons.aaru.edu.jo/fcij/vol4/iss2/1