An Extended Symbol Table Infrastructure to Manage the Composition of Output-Specific Generator Information
This work addresses a specific bottleneck in model-driven development for software engineers, but it is incremental as it builds on existing symbol table approaches.
The paper tackles the challenge of managing output-specific information in template-based code generation by proposing an extended symbol table infrastructure to explicitly model and store parts of the generated output, enabling access during code generation to ensure valid composition of source code.
Code generation is regarded as an essential part of model-driven development (MDD) to systematically transform the abstract models to concrete code. One current challenges of templatebased code generation is that output-specific information, i.e., information about the generated source code, is not explicitly modeled and, thus, not accessible during code generation. Existing approaches try to either parse the generated output or store it in a data structure before writing into a file. In this paper, we propose a first approach to explicitly model parts of the generated output. These modeled parts are stored in a symbol for efficient management. During code generation this information can be accessed to ensure that the composition of the overall generated source code is valid. We achieve this goal by creating a domain model of relevant generator output information, extending the symbol table to store this information, and adapt the overall code generation process.