Semantic Interpretation of Requirements through Cognitive Grammar and Configuration

摘要

Many attempts have been made to apply Natural Language Processing to requirements specifications. However, typical approaches rely on shallow parsing to identify object-oriented elements of the specifications (e.g. classes, attributes, and methods). As a result, the models produced are often incomplete, imprecise, and require manual revision and validation. In contrast, we propose a deep Natural Language Understanding approach to create complete and precise formal models of requirements specifications. We combine three main elements to achieve this: (1) acquisition of lexicon from a user-supplied glossary requiring little specialised prior knowledge; (2) flexible syntactic analysis based purely on word-order; and (3) Knowledge-based Configuration unifies several semantic analysis tasks and allows the handling of ambiguities and errors. Moreover, we provide feedback to the user, allowing the refinement of specifications into a precise and unambiguous form. We demonstrate the benefits of our approach on an example from the PROMISE requirements corpus.