Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/11437
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dc.contributor.authorDeval,Len
dc.contributor.authorBordignon,Men
dc.contributor.authorKahl,Ben
dc.contributor.authorAndré Filipe Santosen
dc.contributor.authorLuedtke,Men
dc.contributor.authorGarcia,NHen
dc.contributor.other6414en
dc.date.accessioned2020-07-17T16:15:46Z-
dc.date.available2020-07-17T16:15:46Z-
dc.date.issued2019en
dc.identifier.urihttp://repositorio.inesctec.pt/handle/123456789/11437-
dc.identifier.urihttp://dx.doi.org/10.1109/models.2019.00-11en
dc.description.abstractIn principle, Model-Driven Engineering (MDE) addresses central aspects of robotics software development. Domain experts could leverage the expressiveness of models; implementation details over different hardware could be handled by automatic code generation. In practice, most evidence points to manual code development as the norm, despite several MDE efforts in robotics. Possible reasons for this disconnect are the wide ranges of applications and target platforms making all-encompassing MDE IDEs hard to develop and maintain, with developers reverting to writing code manually. Acknowledging this, and given the opportunity to leverage a large corpus of open-source software widely adopted by the robotics community, we pursue modeling as a complement, rather than an alternative, to manually written code. Our previous work introduced metamodels to describe components, their interactions, and their resulting composition, as inspired by, but not limited to, the de-facto standard Robot Operating System (ROS). In this paper we put such metamodels into use through two contributions [1]. First, we automate the generation of models from manually written artifacts through extraction from source code and runtime system monitoring. Second, we make available an easy-to-use web infrastructure to perform the extraction, together with a growing database of models so generated. Our aim with this tooling, publicly available both as-a-service and as source code, is to lower the MDE barrier for practitioners and leverage models to 1) improve the understanding of manually written code; 2) perform correctness checks; and 3) systematize the definition and adoption of best practices through large-scale generation of models from existing code. A comprehensive example is provided as a walk-through for robotics software practitioners.en
dc.languageengen
dc.titleBootstrapping MDE Development from ROS Manual Code - Part 2: Model Generationen
dc.typePublicationen
dc.typeconferenceObjecten
Appears in Collections:HASLab - Indexed Articles in Conferences

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