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Programming cocktail analysis based on the cognitive load theory, a first approach

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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.fosHumanidades::Línguas e Literaturas
datacite.subject.sdg04:Educação de Qualidade
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorCosta Neto, Alvaro
dc.contributor.authorPereira, Maria João
dc.contributor.authorHenriques, Pedro Rangel
dc.date.accessioned2026-03-18T14:56:24Z
dc.date.available2026-03-18T14:56:24Z
dc.date.issued2025
dc.description.abstractThe daily activities of those involved in software development are inherently related to the technologies they use. Languages, libraries, frameworks, and tools tend to accumulate as projects evolve and change, effectively forming Programming Cocktails. Unfortunately, the burden of learning, using, and managing these technologies also tends to closely follow this growth, spawning a myriad of concepts that need to be handled concurrently. This complexity usually requires several factors to be analysed, in order to limit its negative effects. These factors range from security risks to costs and cognitive load, just to mention a few. This paper presents an ontology-based modelling framework that can be used to create an overview of Programming Cocktails. The instantiation of this ontology results in Cocktail Identity Cards, which can then be augmented with one or more of the previously mentioned factors. Finally, the paper also presents a first approach to the cognitive load analysis of Programming Cocktails, based on John Sweller’s Cognitive Load Theory.eng
dc.description.sponsorshipThis work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. The work of Maria João and Alvaro was supported by national funds through FCT/MCTES (PIDDAC): CeDRI, UIDB/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and UIDP/05757/2020 (DOI: 10.54499/UIDP/05757/2020); SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020).
dc.identifier.citationCosta Neto, Alvaro; Pereira, Maria João; Henriques, Pedro Rangel (2025). Programming Cocktail Analysis Based on the Cognitive Load Theory, a First Approach. In Topical Area: Software, System and Service Engineering, S3E 2024, Held as Part of FedCSIS 2024, and 25th Conference on Practical Aspects of and Solutions for Software Engineering, KKIO 2024, held as part of SEAA 2024. Cham:Springer Nature. p. 135-164. ISSN 1865-1348. DOI: 10.1007/978-3-031-84913-8_6
dc.identifier.doi10.1007/978-3-031-84913-8_6
dc.identifier.issn1865-1348
dc.identifier.urihttp://hdl.handle.net/10198/36133
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature
dc.relationALGORITMI Research Center
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.relation.ispartofLecture Notes in Business Information Processing
dc.relation.ispartofSoftware, System, and Service Engineering
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/
dc.subjectProgramming cocktails
dc.subjectCognitive load theory
dc.subjectTech stack
dc.subjectProgramming technologies
dc.subjectDevelopment complexity
dc.titleProgramming cocktail analysis based on the cognitive load theory, a first approacheng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardNumberUIDB/00319/2020
oaire.awardNumberUIDB/05757/2020
oaire.awardNumberUIDP/05757/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardTitleALGORITMI Research Center
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.conferencePlaceBelgrade
oaire.citation.endPage164
oaire.citation.startPage135
oaire.citation.titleTopical Area: Software, System and Service Engineering, S3E 2024, Held as Part of FedCSIS 2024, and 25th Conference on Practical Aspects of and Solutions for Software Engineering, KKIO 2024, held as part of SEAA 2024
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNamePereira
person.givenNameMaria João
person.identifier.ciencia-idC912-4A49-A3B3
person.identifier.orcid0000-0001-6323-0071
person.identifier.ridG-5999-2011
person.identifier.scopus-author-id13907870300
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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