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      <dc:title>Analysis and optimisation of SPL products using goal models.</dc:title>
      <dc:creator>Ayala-Viñas, Inmaculada</dc:creator>
      <dc:creator>Amor-Pinilla, María Mercedes</dc:creator>
      <dc:creator>Fuentes-Fernández, Lidia</dc:creator>
      <dc:subject>Programación lineal</dc:subject>
      <dc:subject>Soporte lógico - Desarrollo</dc:subject>
      <dc:description>https://conf.researchr.org/details/RE-2023/RE-2023-Research-Papers/10/Analysis-and-optimisation-of-SPL-products-using-goal-models</dc:description>
      <dc:description>The Internet of Things is one of the core drivers of variability modelling and requires explicit mechanisms to manage&#xd;
it. A key technology for addressing this variability is product line engineering. This approach uses a reference architecture&#xd;
to establish a well-designed set of assets that fit together, the Software Product Line (SPL). One of the limitations of variability&#xd;
models is they do not provide information about the quality of new products or how they achieve stakeholder requirements.&#xd;
Several approaches tackle this issue by integrating variability models with goal models. The main challenge is conciliating the&#xd;
different variability perspectives to make the joint use of both models possible without the loss of information or alterations to&#xd;
the models’ semantics. In this work, we present a framework for analysing and optimising SPL products considering stakeholders’&#xd;
requirements that respects the semantics of both models. The framework is based on Integer Linear Programming (ILP), a&#xd;
field of mathematical programming. Variability and goal models are formalised as a set of linear constraints and are linked using&#xd;
mapping functions. As a proof of concept, we present a tool that takes both models and mapping functions to generate an ILP&#xd;
problem that can be solved using Matlab.</dc:description>
      <dc:date>2023-09-26T11:13:48Z</dc:date>
      <dc:date>2023-09-26T11:13:48Z</dc:date>
      <dc:date>2023-09-04</dc:date>
      <dc:date>2023</dc:date>
      <dc:type>conference output</dc:type>
      <dc:identifier>https://hdl.handle.net/10630/27670</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:relation>31st IEEE International Requirements Engineering 2023 conference</dc:relation>
      <dc:relation>Hannover, Alemania</dc:relation>
      <dc:relation>04/09/2023</dc:relation>
      <dc:rights>http://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
      <dc:rights>open access</dc:rights>
      <dc:rights>Attribution-NonCommercial-NoDerivatives 4.0 Internacional</dc:rights>
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