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dc.creatorMéndez Porras, Abel
dc.creatorAlfaro Velásco, Jorge
dc.creatorJenkins Coronas, Marcelo
dc.creatorMartínez Porras, Alexandra
dc.date.accessioned2018-01-18T16:09:47Z
dc.date.available2018-01-18T16:09:47Z
dc.date.issued2016-08
dc.identifier.citationhttp://www.clei.org/cleiej/paper.php?id=357es_ES
dc.identifier.issn0717- 5000
dc.identifier.urihttp://hdl.handle.net/10669/73879
dc.description.abstractMobile applications support a set of user-interaction features that are independent of the application logic. Rotating the device, scrolling, or zooming are examples of such features. Some bugs in mobile applications can be attributed to user-interaction features. Objective: This paper proposes and evaluates a bug analyzer based on userinteraction features that uses digital image processing to find bugs. Method: Our bug analyzer detects bugs by comparing the similarity between images taken before and after a user-interaction. SURF, an interest point detector and descriptor, is used to compare the images. To evaluate the bug analyzer, we conducted a case study with 15 randomly selected mobile applications. First, we identified user-interaction bugs by manually testing the applications. Images were captured before and after applying each user-interaction feature. Then, image pairs were processed with SURF to obtain interest points, from which a similarity percentage was computed, to finally decide whether there was a bug. Results: We performed a total of 49 user-interaction feature tests. When manually testing the applications, 17 bugs were found, whereas when using image processing, 15 bugs were detected. Conclusions: 8 out of 15 mobile applications tested had bugs associated to user-interaction features. Our bug analyzer based on image processing was able to detect 88% (15 out of 17) of the user-interaction bugs found with manual testing.es_ES
dc.description.sponsorshipUniversidad de Costa Rica/[]/UCR/Costa Ricaes_ES
dc.description.sponsorshipMinisterio de Ciencia, Tecnología t Telecomunicaciones/[]/MICITT/Costa Ricaes_ES
dc.description.sponsorshipInstituto Tecnológico de Costa Rica/[]/TEC/Costa Ricaes_ES
dc.language.isoen_USes_ES
dc.sourceCLEI Electronic Journal, Volume 19, Número 2. 2016es_ES
dc.subjectBug analyzer,es_ES
dc.subjectUser-interaction featureses_ES
dc.subjectImage processinges_ES
dc.subjectInterest pointses_ES
dc.subjectTestinges_ES
dc.titleA user interaction bug analyzer based on image processinges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.typeArtículo científicoes_ES
dc.description.procedenceUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ingeniería::Centro de Investigaciones en Tecnologías de Información y Comunicación (CITIC)es_ES


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