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Log-based User Interface Antipatterns Discovery

Student: Manukhina Yana

Supervisor: Irina A. Lomazova

Faculty: Faculty of Computer Science

Educational Programme: System and Software Engineering (Master)

Year of Graduation: 2016

Success of any software product depends on a number of aspects including its functionality, quality, cost, market-entry time and demand. Among different factors, however, usability and user experience are accepted by most as critical, since they influence user's perception of the product directly. In this work a catalogue of UI antipatterns is assembled and utilized to motivate usability improvements. The idea behind this approach is to derive user behaviour models from real event data. These models can be then analysed to discover behaviour correspondent to predefined user interface issues or antipatterns. Since we do not observe the user directly during the evaluation of existing system usage, there is a challenge of extracting relevant information from large amounts of data and interpreting it to obtain meaningful and reliable insights into user behaviour. The main result of this work is the UI antipatterns catalogue. Each antipattern in this catalogue is characterized by a description of the antipattern itself and the corresponding user behaviour. Discovery methods were identified for each of the antipatterns, some of them, however, could not be automated. Also, suggestions on improving usability were proposed for each antipattern. During this work it became clear that a unified approach towards discovery of UI antipatterns requires expert knowledge of the application due to their diversity and variability of potential usage patterns. Proxy approaches to acquire this knowledge, e.g. by traversing the DOM tree, allow to increase the number of issues that can be detected and the confidence of discovery, but are not universal. Therefore an integrated approach combining different sources should be used for holistic analysis. Among other considerations, potential applicability for industry was evaluated and the requirements for a comprehensive UI analysis framework were identified.

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