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Model-Based Generation of Natural Language Specifications

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Software Technologies: Applications and Foundations (STAF 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9946))

Abstract

Application of formal models provides many benefits for the software and system development, however, the learning curve of formal languages could be a critical factor for an industrial project. Thus, a natural language specification that reflects all the aspects of the formal model might help to understand the model and be especially useful for the stakeholders who do not know the corresponding formal language. Moreover, an automated generation of the documentation from the model would replace manual updates of the documentation for the cases the model is modified. This paper presents an ongoing work on generating natural language specifications from formal models. Our goal is to generate documentation in English from the basic modelling artefacts, such as data types, state machines, and architectural components. To allow further formal analysis of the generated specification, we restrict English to its subset, Attempto Controlled English.

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Authors and Affiliations

  1. RMIT University, Melbourne, Australia

    Phan Thu Nhat Vo & Maria Spichkova

Authors
  1. Phan Thu Nhat Vo
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  2. Maria Spichkova
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Correspondence to Maria Spichkova .

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Editors and Affiliations

  1. Dipartimento di Informatica, Universita di Pisa, Pisa, Italy

    Paolo Milazzo

  2. Budapest University of Technology and Economics, Budapest, Hungary

    Dániel Varró

  3. Vienna University of Technology, Vienna, Austria

    Manuel Wimmer

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Vo, P.T.N., Spichkova, M. (2016). Model-Based Generation of Natural Language Specifications. In: Milazzo, P., Varró, D., Wimmer, M. (eds) Software Technologies: Applications and Foundations. STAF 2016. Lecture Notes in Computer Science(), vol 9946. Springer, Cham. https://doi.org/10.1007/978-3-319-50230-4_16

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  • DOI: https://doi.org/10.1007/978-3-319-50230-4_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50229-8

  • Online ISBN: 978-3-319-50230-4

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