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dc.contributor.authorEbert, Christof
dc.contributor.authorHeidrich, Jens
dc.contributor.authorMartínez Fernández, Silverio Juan
dc.contributor.authorTrendowicz, Adam
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
dc.date.accessioned2020-02-13T09:30:05Z
dc.date.available2020-02-13T09:30:05Z
dc.date.issued2019-11
dc.identifier.citationEbert, C. [et al.]. Data science: technologies for better software. "IEEE software", Novembre 2019, vol. 36, núm. 6, p. 66-72.
dc.identifier.issn0740-7459
dc.identifier.otherhttp://www.essi.upc.edu/~smartinez/wp-content/papercite-data/pdf/ebert2019data-science.pdf
dc.identifier.urihttp://hdl.handle.net/2117/177605
dc.description.abstractData science is mandatory in today's business to capitalize on achievements and assets. This specifically holds for modern software development, where data science facilitates analyzing product, process, and usage and thus managing evolution and performance. With the convergence of embedded and IT domains, such as the Internet of Things (IoT) and automotive systems, software systems are becoming more complex. Complexity has two faces. On one hand it means more functionality and fluid delivery models, thus offering markets more value, such as the ability to deliver a single-customer focus. Complexity, however, also means the growth of technical debt, which slows productivity and lowers quality. As software engineering generates ever larger and more varied data sets, such as feature usage, code analysis, test coverage, error logs, and maintenance data, companies face the challenge of unlocking the value of that data.
dc.format.extent7 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Enginyeria del software
dc.subject.lcshSoftware measurement
dc.subject.lcshComputer software -- Development
dc.subject.otherSoftware tools
dc.subject.otherData science
dc.subject.otherComplexity theory
dc.subject.otherAnalytical models
dc.titleData science: technologies for better software
dc.typeArticle
dc.subject.lemacProgramari -- Mesurament
dc.subject.lemacProgramari -- Desenvolupament
dc.contributor.groupUniversitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering
dc.identifier.doi10.1109/MS.2019.2933681
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8880036
dc.rights.accessOpen Access
local.identifier.drac26905693
dc.description.versionPostprint (author's final draft)
local.citation.authorEbert, C.; Heidrich, J.; Martínez-Fernández, S.; Trendowicz, A.
local.citation.publicationNameIEEE software
local.citation.volume36
local.citation.number6
local.citation.startingPage66
local.citation.endingPage72


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