Abstract-In times of ever-growing system complexity and thus increasing possibilities for errors, high-quality requirements are crucial to prevent design errors in later project phases and to facilitate design verification and validation. To ensure and improve the consistency, completeness and correctness of requirements, formal languages have been introduced as an alternative to using natural language (NL) requirement descriptions. However, in many cases existing NL requirements must be taken into account. The formalization of those requirements by now is a primarily manual task, which therefore is both cumbersome and error-prone. We introduce the tool DODT that semi-automatically transforms NL requirements into semiformal boilerplate requirements. The transformation builds upon a domain ontology (DO) containing knowledge of the problem domain and upon natural language processing techniques. The tool strongly reduced the required manual effort for the transformation. In addition the quality of the requirements was improved.

Abstract. Requirements managers aim at keeping their sets of requirements well-defined, consistent and up to date throughout a project's life cycle. Semantic web technologies have found many valuable applications in the field of requirements engineering, with most of them focusing on requirements analysis. However the usability of results originating from such requirements analyses strongly depends on the quality of the original requirements, which often are defined using natural language expressions without meaningful structures. In this work we present the prototypic implementation of a semantic guidance system used to assist requirements engineers with capturing requirements using a semi-formal representation. The semantic guidance system uses concepts, relations and axioms of a domain ontology to provide a list of suggestions the requirements engineer can build on to define requirements. The semantic guidance system is evaluated based on a domain ontology and a set of requirements from the aerospace domain. The evaluation results show that the semantic guidance system supports the requirements engineer in defining well-structured requirements.

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