--- res: bibo_abstract: - 'While requirements focus on how the user interacts with the system, user stories concentrate on the purpose of software features. But in practice, functional requirements are also described in user stories. For this reason, requirements clarification is needed, especially when they are written in natural language and do not stick to any templates (e.g., "as an X, I want Y so that Z ..."). However, there is a lot of implicit knowledge that is not expressed in words. As a result, natural language requirements descriptions may suffer from incompleteness. Existing approaches try to formalize natural language or focus only on entirely missing and not on deficient requirements. In this paper, we therefore present an approach to detect knowledge gaps in user-generated software requirements for interactive requirement clarification: We provide tailored suggestions to the users in order to get more precise descriptions. For this purpose, we identify not fully instantiated predicate argument structures in requirements written in natural language and use context information to realize what was meant by the user.@eng' bibo_authorlist: - foaf_Person: foaf_givenName: Frederik Simon foaf_name: Bäumer, Frederik Simon foaf_surname: Bäumer foaf_workInfoHomepage: http://www.librecat.org/personId=38837 - foaf_Person: foaf_givenName: Michaela foaf_name: Geierhos, Michaela foaf_surname: Geierhos foaf_workInfoHomepage: http://www.librecat.org/personId=42496 orcid: 0000-0002-8180-5606 bibo_doi: 10.1007/978-3-319-46254-7_44 bibo_volume: 639 dct_date: 2016^xs_gYear dct_isPartOf: - http://id.crossref.org/issn/978-3-319-46253-0 dct_language: eng dct_publisher: Springer@ dct_subject: - Natural language requirements clarification - Syntactically incomplete requirements - Compensatory user stories dct_title: 'Running out of Words: How Similar User Stories Can Help to Elaborate Individual Natural Language Requirement Descriptions@' ...