A distributed bug analyzer based on user-interaction features for mobile apps

Tipo de publicación: Journal Article

Publicado en: Journal of Ambient Intelligence and Humanized Computing

Autores
  • Méndez-Porras, Abel
  • Méndez-Marín, Giovanni
  • Tablada-Rojas, Alberto
  • Hidalgo, Mario Nieto
  • García-Chamizo, Juan Manuel
  • Jenkins, Marcelo
  • Martínez, Alexandra

Investigadores del CITIC asociados a la publicación
Dra. Alexandra Martínez Porras
Dr. Marcelo Jenkins Coronas
Abel Méndez Porras

Proyecto asociado a la publicación
Evaluación de herramientas automatizadas para pruebas de software basadas en modelos

Palabras claves
  • Automated testing
  • Digital imaging processing
  • Distributed bug analyzer
  • Interest points
  • User-interaction features
Resumen

Developers must spend more effort and attention on the processes of software development to deliver quality applications to the users. Software testing and automation play a strategic role in ensuring the quality of mobile applications. This paper proposes and evaluates a Distributed Bug Analyzer based on user-interaction features that uses digital imaging processing to find bugs. Our Distributed Bug Analyzer detects bugs by comparing the similarity between images taken before and after an user-interaction feature occurs. An interest point detector and descriptor is used for image comparison. To evaluate the Distribute Bug Analyzer, we conducted a case study with 38 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 (using SURF) to obtain interest points, from which a similarity percentage was computed, to identify the presence of bugs. We used a Master Computer, a Storage Test Database, and four Slave Computers to evaluate the Distributed Bug Analyzer. We performed 360 tests of user-interaction features in total. We found 79 bugs when manually testing user-interaction features, and 69 bugs when using digital imaging processing to detect bugs with a threshold fixed at 92.5{%} of similarity. Distributed Bug Analyzer evenly distributed tests that are pending in the Storage Test Database between the Slave Computers. Slave Computers 1, 2, 3, and 4 processed 21, 20, 23, and 36{%} of image pair respectively.

DOI BIBTEXT

Datos bibliográficos
Cita bibliográfica
A distributed bug analyzer based on user-interaction features for mobile apps