Analysis and measurement of internal usability metrics through code annotations
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
Springer VerlagDate
2019-07-04Citation
Software Quality Journal 27.4 (2019): 1505–1530ISSN
0963-9314 (print); 1573-1367 (online)Funded by
This work was partially supported by the Madrid Research Council (P2018/TCS-4314)Project
Comunidad de Madrid. P2018/TCS-4314Editor's Version
https://link.springer.com/article/10.1007/s11219-019-09455-4; https://doi.org/10.1007/s11219-019-09455-4Subjects
Internal Software-Product Quality; Usability Metric; Code Annotation; User-Centered Development; Human-Computer Interaction; InformáticaNote
This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11219-019-09455-4Rights
© 2019, Springer Science+Business Media, LLC, part of Springer NatureAbstract
Nowadays, usability can be meant as an important quality characteristic to be considered throughout the software development process. A great variety of usability techniques have been proposed so far, mostly intended to be applied during analysis, design and final testing phases in software projects.
However, little or no attention has been paid to the analysis and measurement of usability in the implementation phase. Most of the time, usability testing is traditionally executed in advanced stages. However, the detection of usability flaws during the implementation is of utmost importance to foresee and prevent problems in the utilization of the software and avoid significant cost increases. In
this paper, we propose a feasible solution to analyze and measure usability metrics during the implementation phase. Specifically, we have developed a framework featuring code annotations that provides a systematic evaluation of the usability throughout the source code. These annotations are interpreted by an annotation processor to obtain valuable information and automatically calculate usability metrics at compile time. In addition, an evaluation with 32 participants has been carried out to demonstrate the effectiveness and efficiency of our approach in comparison to the manual process of analyzing and measuring internal usability metrics. Perceived satisfaction was also evaluated, demonstrating that our approach can be considered as a valuable tool for dealing with usability metrics
during the implementation phase
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Google Scholar:Schramme, Maximilian
-
Macías Iglesias, José Antonio
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