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Software Knowledge Representation to Understand Software Systems

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Software Knowledge Representation to Understand Software Systems

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dc.contributor.author Torres Bosch, Maria Victoria es_ES
dc.contributor.author Gil Pascual, Miriam es_ES
dc.contributor.author Pelechano Ferragud, Vicente es_ES
dc.date.accessioned 2019-12-09T08:58:44Z
dc.date.available 2019-12-09T08:58:44Z
dc.date.issued 2019-11-18
dc.identifier.isbn 978-3-030-35332-2
dc.identifier.uri http://hdl.handle.net/10251/132515
dc.description.abstract A software development process involves numerous persons, including customers, domain experts, software engineers, managers, evaluators and certifiers. Together, they produce some software that satisfies its requirements and its quality criteria at a certain point in time. This software contains faults and flaws of different levels of severity and at different phases of its production (specification, design, etc.) so maintenance is needed in order to correct it. Perfective and adaptive maintenance is also needed to cope with changes in the environment or with new requirements, e.g. new functionalities. In this work, we introduce the Persistent Knowledge Monitor (PKM), which is being developed within the DECODER H2020 project for handling (i.e. storing, retrieving, merging and checking for consistency) all kinds of knowledge and information related to a software project. The PKM will be part of a platform capable of taking advantage of all the artefacts available in a software ecosystem, not only the source code, but also its version control system, abstract specifications, informal documents or reports, etc. for representing the software knowledge and improving the workflow of software developers. es_ES
dc.description.sponsorship This work has been developed with the financial support of the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 824231 and the Spanish State Research Agency under the project TIN2017-84094-R and co-financed with ERDF. es_ES
dc.format.extent 8 es_ES
dc.language Inglés es_ES
dc.publisher Springer es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Persistent Knowledge Monitor es_ES
dc.subject Software engineering es_ES
dc.subject Traceability es_ES
dc.subject.classification BIBLIOTECONOMIA Y DOCUMENTACION es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Software Knowledge Representation to Understand Software Systems es_ES
dc.type Capítulo de libro es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1007/978-3-030-35333-9_10
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-84094-R/ES/DISEÑO DE SISTEMAS AUTO-ADAPTATIVOS INVOLUCRANDO AL HUMANO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/824231/EU/DEveloper COmpanion for Documented and annotatEd code Reference/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Torres Bosch, MV.; Gil Pascual, M.; Pelechano Ferragud, V. (2019). Software Knowledge Representation to Understand Software Systems. Springer. 137-144. https://doi.org/10.1007/978-3-030-35333-9_10 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 20th International Conference of Product-Focused Software Development and Process Improvement (PROFES 2019) es_ES
dc.relation.conferencedate Noviembre 27-29,2019 es_ES
dc.relation.conferenceplace Barcelona, Spain es_ES
dc.relation.publisherversion https://doi.org/10.1007/978-3-030-35333-9_10 es_ES
dc.description.upvformatpinicio 137 es_ES
dc.description.upvformatpfin 144 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\398458 es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder European Regional Development Fund es_ES


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