Enabling Domain Experts to Modify Formal Models via a Natural Language Representation Consistently (bibtex)
by , , ,
Abstract:
While requirements described in Natural Language are inherently ambiguous and hard to check for consistency, they are intuitively understandable for domain experts. Using formal models, on the other hand, supports requirements engineers to specify requirements correct, consistent and complete. Transformations between these two different representations can become quite complex, since not everything that can be expressed with natural language can be captured in a restricted formal model. We describe a transformation approach that takes the formal modeling operations of story patterns and allows domain experts to transparently apply them on a natural language representation of these formal models. Also, a preliminary evaluation is presented.
Reference:
Enabling Domain Experts to Modify Formal Models via a Natural Language Representation Consistently (Gregor Gabrysiak, Daniel Eichler, Regina Hebig, Holger Giese), In Proc. of the First ICSE 2013 Workshop on Natural Language Analysis in Software Engineering, 2013.
Bibtex Entry:
@InProceedings{GEHG13---NL4SP,
AUTHOR = {Gabrysiak, Gregor and Eichler, Daniel and Hebig, Regina and Giese, Holger},
TITLE = {{Enabling Domain Experts to Modify Formal Models via a Natural Language Representation Consistently}},
YEAR = {2013},
MONTH = {25 May},
BOOKTITLE = {Proc. of the First ICSE 2013 Workshop on Natural Language Analysis in Software Engineering},
SERIES = {NaturaLiSE'13},
PDF = {uploads/pdf/GEHG13---NL4SP_submission.pdf},
OPTacc_pdf = {},
ABSTRACT = {While requirements described in Natural Language are inherently ambiguous and hard to check for consistency, they are intuitively understandable for domain experts. Using formal models, on the other hand, supports requirements engineers to specify requirements correct, consistent and complete. Transformations between these two different representations can become quite complex, since not everything that can be expressed with natural language can be captured in a restricted formal model. We describe a transformation approach that takes the formal modeling operations of story patterns and allows domain experts to transparently apply them on a natural language representation of these formal models. Also, a preliminary evaluation is presented.}
}
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