---
res:
  bibo_abstract:
  - Distributed, software-intensive systems such as fully automated cars have to handle
    various situations employing message-based coordination. The growing complexity
    of such systems results in an increasing difficulty to achieve a high quality
    of the systems’ requirements specifications, particularly w.r.t. the realizability
    of the specifications. Scenario-based requirements engineering addresses the message-based
    coordination of such systems and enables, if underpinned with formal languages,
    automatic requirements validation techniques for proving the realizability of
    a requirements specification. However, formal requirements modeling languages
    require a deep knowledge of requirements engineers and typically require many
    manual iterations until they find a realizable specification. In order to support
    requirements engineers in the stepwise development of scenario-based requirements
    specifications, we propose to evolve a high-quality specification from a (presumably
    unrealizable) manually created specification employing an evolutionary algorithm.
    In this paper, we show our results on automatically evolving new assumptions on
    the systems’ environment behavior that guarantee a realizable requirements specification.
    Based on this contribution, we outline our research roadmap toward our long-term
    goal of automatically supporting requirements engineers in finding high-quality
    requirements specifications.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: David
      foaf_name: Schmelter, David
      foaf_surname: Schmelter
      foaf_workInfoHomepage: http://www.librecat.org/personId=40982
    orcid: 0000-0001-7787-5380
  - foaf_Person:
      foaf_givenName: Joel
      foaf_name: Greenyer, Joel
      foaf_surname: Greenyer
  - foaf_Person:
      foaf_givenName: Jörg
      foaf_name: Holtmann, Jörg
      foaf_surname: Holtmann
      foaf_workInfoHomepage: http://www.librecat.org/personId=3875
    orcid: 0000-0001-6141-4571
  bibo_doi: 10.1109/REW.2017.14
  dct_date: 2017^xs_gYear
  dct_language: eng
  dct_publisher: IEEE@
  dct_title: Toward Learning Realizable Scenario-based, Formal Requirements Specifications@
...