Code generation by example

Code generation is a key technique for model-driven engineering approaches of software construction. Code generation enables the synthesis of applications in executable programming languages from high-level specifications in UML or a domain-specific language. Specialised code-generation languages and tools have been defined, such as Epsilon EGL and Acceleo, however the task of writing a code generator remains a substantial undertaking, requiring a high degree of expertise in both the source and target languages, and in the code-generation language. In this paper we show how symbolic machine learning techniques can be used to reduce the time and effort for developing code generators. We apply the techniques to the development of a UML-to-Java code generator.