Predicting web service maintainability via object-oriented metrics: A statistics-based approach

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dc.authorscopusid55303736600
dc.authorscopusid15073886400
dc.authorscopusid24171844000
dc.authorscopusid8688799600
dc.authorscopusid56962766700
dc.contributor.authorMısra, Sanjay
dc.contributor.authorCrasso,M.
dc.contributor.authorMateos,C.
dc.contributor.authorZunino,A.
dc.contributor.authorMisra,S.
dc.contributor.otherComputer Engineering
dc.date.accessioned2024-07-05T15:43:52Z
dc.date.available2024-07-05T15:43:52Z
dc.date.issued2012
dc.departmentAtılım Universityen_US
dc.department-tempCoscia J.L.O., UNICEN University, Tandil, Argentina; Crasso M., ISISTAN Research Institute, Tandil, Argentina, UNICEN University, Tandil, Argentina, Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Argentina; Mateos C., ISISTAN Research Institute, Tandil, Argentina, UNICEN University, Tandil, Argentina, Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Argentina; Zunino A., ISISTAN Research Institute, Tandil, Argentina, UNICEN University, Tandil, Argentina, Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), Argentina; Misra S., Department of Computer Engineering, Atilim University, Ankara, Turkeyen_US
dc.descriptionUniversidade Federal da Bahia (UFBA); Universidade Federal do Reconcavo da Bahia (UFRB); Universidade Estadual de Feira de Santana (UEFS); University of Perugia; University of Basilicata (UB)en_US
dc.description.abstractThe Service-Oriented Computing paradigm enables the construction of distributed systems by assembling loosely coupled pieces of software called services, which have clear interfaces to their functionalities. Service interface descriptions have many aspects, such as complexity and quality, all of which can be measured. This paper presents empirical evidence showing that services interfaces maintainability can be predicted by applying traditional software metrics in service implementations. A total of 11 source code level metrics and 5 service interface metrics have been statistically correlated using 154 real world services. © 2012 Springer-Verlag.en_US
dc.identifier.citation13
dc.identifier.doi10.1007/978-3-642-31128-4_3
dc.identifier.endpage39en_US
dc.identifier.isbn978-364231127-7
dc.identifier.issn1611-3349
dc.identifier.issuePART 4en_US
dc.identifier.scopus2-s2.0-84863959084
dc.identifier.startpage29en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-642-31128-4_3
dc.identifier.urihttps://hdl.handle.net/20.500.14411/3680
dc.identifier.volume7336 LNCSen_US
dc.language.isoenen_US
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -- 12th International Conference on Computational Science and Its Applications, ICCSA 2012 -- 18 June 2012 through 21 June 2012 -- Salvador de Bahia -- 90945en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCode-Firsten_US
dc.subjectObject-Oriented Metricsen_US
dc.subjectService-Oriented Computingen_US
dc.subjectWeb Service Maintainabilityen_US
dc.subjectWeb Service Maintainability Predictionen_US
dc.subjectWeb Servicesen_US
dc.titlePredicting web service maintainability via object-oriented metrics: A statistics-based approachen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscovery53e88841-fdb7-484f-9e08-efa4e6d1a090
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relation.isOrgUnitOfPublication.latestForDiscoverye0809e2c-77a7-4f04-9cb0-4bccec9395fa

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