An Extended Symbol Table Infrastructure to Manage the Composition of Output-Specific Generator Information

TL;DR

This paper introduces an extended symbol table infrastructure that explicitly models and manages output-specific information during code generation, improving the validity and composition of generated source code in model-driven development.

Contribution

It presents a novel approach to explicitly model output-specific generator information using an extended symbol table, enhancing code generation processes.

Findings

Efficient management of generated output information.

Improved validity of composed source code.

Enhanced accessibility to output details during code generation.

Abstract

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.