Python Training by Dan Bader

Towards Automated Detection of Mobile Usability Issues

Paper and supporting materials for a talk I gave at the “1st European Workshop on Mobile Engineering” in February 2013 at RWTH Aachen.


This is the paper that Dennis Pagano and I submitted to the ME‘13 workshop. The workshop was a part of the SE‘13 software engineering conference at RWTH Aachen.

Abstract: While evaluating the usability of mobile applications in the field has proven to lead to better results than in laboratory settings, in practice it is still not carried out after deployment – typically due to the required resources. In this paper we demonstrate a lightweight automated method for revealing specific usability issues of mobile applications in the field. Based on application usage data, we derive a simple heuristic which detects low discoverability by analyzing view transitions of mobile applications at runtime. We show the applicability and feasibility of our approach in a user study with a real application. Our results are promising and call for further research.

You can read the paper in the conference proceedings (PDF, pp. 341 - 354).

Sample code

The proof of concept implementation of the low discoverability detection heuristic together with a demo application is available as source code on GitHub.

Presentation slides

The presentation slides of our workshop talk are available on Speaker Deck.

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This article was filed under: academia, iOS, objective-c, programming, and usability.

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