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Delta GUI change detection using inferred models

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dc.contributor.author Pastor-Ricós, Fernando es_ES
dc.contributor.author Marín-Campusano, Beatriz Mariela es_ES
dc.contributor.author Vos, Tanja Ernestina es_ES
dc.contributor.author Neeft, Rick es_ES
dc.contributor.author Aho, Pekka es_ES
dc.date.accessioned 2025-02-27T19:02:49Z
dc.date.available 2025-02-27T19:02:49Z
dc.date.issued 2025-03 es_ES
dc.identifier.issn 0920-5489 es_ES
dc.identifier.uri http://hdl.handle.net/10251/214912
dc.description.abstract [EN] Recent software development methodologies emphasize iterative and incremental evolution to align with stakeholders' needs. This perpetual and rapid software evolution demands ongoing research into verification practices and technologies that ensure swift responsiveness and effective management of software delta increments. Strategies such as code review have been widely adopted for development and verification, ensuring readability and consistency in the delta increments of software projects. However, the integration of techniques to detect and visually report delta changes within the Graphical User Interface (GUI) software applications remains an underutilized process. In this paper, we set out to achieve two objectives. First, we aim to conduct a comprehensive review of existing studies concerning GUI change detection in desktop, web, and mobile applications to recognize common practices. Second, we introduce a novel change detection tool capable of highlighting delta GUI changes for this diverse range of applications. To accomplish our first objective, we performed a systematic mapping of the literature using the Scopus database. To address the second objective, we designed and developed a GUI change detection tool. This tool simultaneously transits and compares state models inferred by a scriptless testing tool, enabling the detection and highlighting of GUI changes to detect the widgets or functionalities that have been added, removed, or modified. Our study reveals the existence of a multitude of techniques for change detection in specific GUI systems with different objectives. However, there is no widely adopted technique suitable for the diverse range of existing desktop, web, and mobile applications. Our tool and findings demonstrate the effectiveness of using inferred state models to highlight between 8 and 20 GUI changes in software delta increments containing a large number of changes over months and between 4 and 6 GUI changes in delta increments of small iterations performed over multiple weeks. Moreover, some of these changes were recognized by the software developers as GUI failures that required a fix. Finally, we expose the motivation for using this technique to help developers and testers analyze GUI changes to validate delta increments and detect potential GUI failures, thereby fostering knowledge dissemination and paving the way to standard practices. es_ES
dc.description.sponsorship This research has been funded by the project European Innovation Alliance for Testing Education (ENACTEST) , ERASMUS+ number 101055874, 2022-2025. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Computer Standards & Interfaces es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Delta validation es_ES
dc.subject GUI change detection es_ES
dc.subject Scriptless testing es_ES
dc.subject State Model inference es_ES
dc.subject Systematic mapping es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Delta GUI change detection using inferred models es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.csi.2024.103925 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/COMISION DE LAS COMUNIDADES EUROPEA//101055874//EUROPEAN INNOVATION ALLIANCE FOR TESTING EDUCATION / es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Pastor-Ricós, F.; Marín-Campusano, BM.; Vos, TE.; Neeft, R.; Aho, P. (2025). Delta GUI change detection using inferred models. Computer Standards & Interfaces. 92. https://doi.org/10.1016/j.csi.2024.103925 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.csi.2024.103925 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 92 es_ES
dc.relation.pasarela S\525463 es_ES
dc.contributor.funder COMISION DE LAS COMUNIDADES EUROPEA es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
upv.costeAPC 2340 es_ES


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