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Customizable automatic detection of bad usability smells in mobile accessed web applications

Published: 04 September 2017 Publication History

Abstract

Remote usability evaluation enables the possibility of analysing users' behaviour in their daily settings. We present a method and an associated tool able to identify potential usability issues through the analysis of client-side logs of mobile Web interactions. Such log analysis is based on the identification of specific usability smells. We describe an example set of bad usability smells, and how they are detected. The tool also allows evaluators to add new usability smells not included in the original set. We also report on the tool use in analysing the usability of a real, widely used application accessed by forty people through their smartphones whenever and wherever they wanted.

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    cover image ACM Conferences
    MobileHCI '17: Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services
    September 2017
    874 pages
    ISBN:9781450350754
    DOI:10.1145/3098279
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 04 September 2017

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    Author Tags

    1. remote usability evaluation
    2. usability bad smells
    3. web mobile application log analysis

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    MobileHCI '17 Paper Acceptance Rate 45 of 224 submissions, 20%;
    Overall Acceptance Rate 202 of 906 submissions, 22%

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    • (2024)Development of Data-driven Persona Including User Behavior and Pain Point through Clustering with User Log of B2B SoftwareProceedings of the 2024 IEEE/ACM 17th International Conference on Cooperative and Human Aspects of Software Engineering10.1145/3641822.3641870(85-90)Online publication date: 14-Apr-2024
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    • (2023)Dynamic detection of accessibility smellsUniversal Access in the Information Society10.1007/s10209-023-01043-5Online publication date: 22-Sep-2023
    • (2022)Definition of Guideline-Based Metrics to Evaluate AAL Ecosystem’s UsabilityHuman Behavior and Emerging Technologies10.1155/2022/89390722022(1-19)Online publication date: 14-Nov-2022
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