Automatic Detection of Usability Smells in Web Applications - Grigera, Julián (2017)
Usability assessment of web applications continues to be an expensive and often neglected practice. While large companies are able to spare resources for studying and improving usability in their products, smaller businesses often divert theirs in other aspects. To help these cases, researches have devised automatic approaches for user interaction analysis, and there are commercial services that offer automated usability statistics at relatively low fees. However, most existing approaches still fall short in specifying the usability problems concretely enough to identify and suggest solutions. In this work we describe usability smells of user interaction, i.e., hints of usability problems on running web applications, and the process in which they can be iden tified by analyzing user interaction events. We also describe USF, the tool that implements the process in a fully automated way with minimum setup effort. USF analyses user interaction events on-the-fly, discovers usability smells and reports them together with a concrete solution in terms of a usability refactoring, providing usability advice for deployed web applications.