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      <dc:title>Combining OCL and Natural Language: a Call for a Community Effort</dc:title>
      <dc:creator>Cabot, Jordi</dc:creator>
      <dc:creator>Delgado, David</dc:creator>
      <dc:creator>Burgueño-Caballero, Lola</dc:creator>
      <dc:subject>Lingüística computacional</dc:subject>
      <dc:description>The growing popularity and availability of pretrained natural language models opens the door to many interesting applications combining natural language (NL) with software artefacts. A couple of examples are the generation of code excerpts from NL instructions or the verbalization of programs in NL to facilitate their comprehension.&#xd;
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Many of these language models have been trained with open source software datasets and therefore understand a variety of programming languages, but not OCL.&#xd;
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We argue that OCL needs to jump into the machine learning bandwagon or it will risk losing its appeal as a constraint specification language. For that, the key first task is to create together an OCL corpus dataset amenable for natural language processing.</dc:description>
      <dc:date>2022-11-07T12:28:50Z</dc:date>
      <dc:date>2022-11-07T12:28:50Z</dc:date>
      <dc:date>2022-10</dc:date>
      <dc:type>conference output</dc:type>
      <dc:identifier>https://hdl.handle.net/10630/25360</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:relation>21st International Workshop on OCL and Textual Modeling (OCL'22) Co-located with MODELS'22</dc:relation>
      <dc:relation>Montréal, Canadá</dc:relation>
      <dc:relation>23/09/2022 - 28/09/2022</dc:relation>
      <dc:rights>open access</dc:rights>
      <dc:publisher>ACM</dc:publisher>
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