A user interaction bug analyzer based on image processing
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| Autores: | , , , |
|---|---|
| Formato: | artículo original |
| Fecha de Publicación: | 2016 |
| Descripción: | Mobile 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. |
| País: | Kérwá |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Kérwá |
| OAI Identifier: | oai:kerwa.ucr.ac.cr:10669/73879 |
| Acceso en línea: | http://www.clei.org/cleiej/paper.php?id=357 https://hdl.handle.net/10669/73879 |
| Palabra clave: | Bug analyzer, User-interaction features Image processing Interest points Testing |