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KLM-GOMS Detection of Interaction Patterns Through the Execution of Unplanned Tasks

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dc.contributor.authorCunha, Daniel
dc.contributor.authorP. Duarte, Rui
dc.contributor.authorCunha, Carlos A.
dc.date.accessioned2023-06-26T09:09:18Z
dc.date.available2023-06-26T09:09:18Z
dc.date.issued2021
dc.description.abstractThe availability of software applications has contributed to the increase in user demand, which has increased the complexity of these applications. This contributed to the adoption of automation mechanisms for the software testing process, in order to reduce coding errors and shorten the time needed to deploy a new version of the application to the user. Currently, automating the application testing process is a well-established reality and supported by many tools. However, the usability evaluation of an application requires solutions that allow to determine, in advance, the type of improvements that may be necessary in the application without the need for intensive user testing. This work deals with the automatic analysis of the impact on the user of changes in the design of an application, through the implementation of the Keystroke Level Model (KLM). Based on the execution of unplanned user interactions in a web interface, a KLM string is obtained and evaluated, providing a model that converts KLM operators and the execution time of each operator into information for designers. Moreover, performance indicators are obtained and interaction patterns are automatically defined.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCunha, D., Duarte, R.P., Cunha, C.A. (2021). KLM-GOMS Detection of Interaction Patterns Through the Execution of Unplanned Tasks. In: , et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science, vol 12950. Springer, Cham. https://doi.org/10.1007/978-3-030-86960-1_15pt_PT
dc.identifier.doi10.1007/978-3-030-86960-1_15pt_PT
dc.identifier.issn978-3-030-86960-1
dc.identifier.urihttp://hdl.handle.net/10400.19/7818
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relationThis work is funded by National Funds through the FCT - Foundation for Science and Technology, I.P., within the scope of the project Ref. UIDB/05583/2020pt_PT
dc.subjectKeystroke level modelpt_PT
dc.subjectHuman-centered computingpt_PT
dc.subjectSoftware Testingpt_PT
dc.subjectInteraction designpt_PT
dc.subjectUser interface designpt_PT
dc.titleKLM-GOMS Detection of Interaction Patterns Through the Execution of Unplanned Taskspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage219pt_PT
oaire.citation.startPage203pt_PT
oaire.citation.titleInternational Conference on Computational Science and Its Applications (ICCSA)pt_PT
oaire.citation.volume12950pt_PT
person.familyNameMonteiro Amaro Duarte
person.givenNameRui Pedro
person.identifiergIYE8M4AAAAJ
person.identifier.ciencia-id211F-55A0-4B63
person.identifier.orcid0000-0002-6819-0985
person.identifier.scopus-author-id14059938600
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationd56c3162-80a4-4ade-810d-43bae4ee6d73
relation.isAuthorOfPublication.latestForDiscoveryd56c3162-80a4-4ade-810d-43bae4ee6d73

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