We recently got a research paper on our work in S-CASE accepted at a workshop on semantic parsing. We propose to automatically map software requirements written in natural language to formal representations, with the goal of reducing emerging problems such as ambiguity and incompleteness. As first steps towards this goal, we present an initial data set of requirements and describe an ontology for representing them conceptually.
Software requirements are commonly written in natural language, making them prone to ambiguity, incompleteness and inconsistency. By converting requirements to formal semantic representations, emerging problems can be detected at an early stage of the development process, thus reducing the number of ensuing errors and the development costs. In this paper, we treat the mapping from requirements to formal representations as a semantic parsing task We describe a novel data set for this task that involves two contributions: first, we establish an ontology for formally representing requirements and second, we introduce an iterative annotation are derived through step-wise refinements.
You can read the abstract of the paper online now.
Michael Roth – The University of Edinburgh
This research paper will appear in:
“Proceedings of the ACL 2014 Workshop on Semantic Parsing (SP14)”,
Baltimore, Maryland, USA,
27 August 2014