Supporting Software Language Engineering by Automated Domain Knowledge Acquisition

摘要

In model-driven engineering, domain-specific languages (DSLs) play an important role in providing well-defined environments for modeling different aspects of a system. Detailed knowledge of the application domain as well as expertise in language engineering is required to create new languages. This research work proposes automated knowledge acquisition to support language engineers in early language development phases. We describe an iterative approach in which DSL development benefits from formalized knowledge sources and information extraction from text supporting domain analysis and metamodel construction. We show how the acquired knowledge is used to guide language engineers and how knowledge acquisition is adapted according to modeling decisions.