Finding usability bugs with automated tests

Harty, Julian

doi:10.1145/1897816.1897836

Cited by 28 publications

(6 citation statements)

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“…Users from various cultures tend to move their eyes differently and focus on different website areas (Blais et al 2008). Much debate has evolved around their ability to simulate human perception (Harty 2011). These tools are based on neuro-science findings, visual attention studies, statistics from eye-tracking sessions, perception and cognition of humans and have been a recent phenomenon (Kondratova and Goldfarb 2009).…”

Section: Methodsmentioning

confidence: 99%

Cultural differences in online beer marketing: findings from automated attention analysis

Kincl

Štrach

2013

Behaviour & Information Technology

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The impact of culture on consumer behaviour has been an important research area for decades. The rise of e-commerce prompted the importance of culturally bound differences between websites. Web designers are compelled to adjust website development to the cultural characteristics of the target audience and to reflect local perspectives. The actual target users are often invited to provide valuable feedback on e-commerce applications. However, user tests are extremely costly and time consuming. Tools for automated web design assessment have only recently been introduced and have provoked debate regarding their ability to simulate human interaction. In this article, 40 leading beer-brand-related websites from four different groups (countries) are analysed. The aim of this study is to discover if automated tools predicting user eye activity are able to distinguish between websites from different cultures. The findings indicate that automated tools provide quick and inexpensive results for initial assessment of the website interface, clearly differentiating between websites from different cultural backgrounds, resonating with the current literature.

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Section: Methodsmentioning

confidence: 99%

Cultural differences in online beer marketing: findings from automated attention analysis

Kincl

Štrach

2013

Behaviour & Information Technology

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“…(1) It is a mature and maintained tool available since several years, deeply documented both online and by specific books ; (2) it is open‐source; (3) it is one of the most widely adopted open‐source solutions for Web test automation (the community of users of the Selenium framework organizes since several years the Selenium Conference in Europe, USA, and India), and it has been used also in several scientific works, eg, to cite a few ; (4) it is being standardized by the W3C ; and (5) during our previous industrial collaborations, we gained a considerable experience in its usage . At the time of writing, we are not aware of Web test automation tools with such characteristics and popularity.…”

Section: Dom‐based and Visual Web Testingmentioning

confidence: 99%

Pesto: Automated migration of DOM‐based Web tests towards the visual approach

Leotta

Stocco

Ricca

et al. 2018

Software Testing Verif & Rel

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Summary Test automation tools are widely adopted for testing complex Web applications. Three generations of tools exist: first, based on screen coordinates; second, based on DOM–based commands; and third, based on visual image recognition. In our previous work, we proposed Pesto, a tool able to migrate second‐generation Selenium WebDriver test suites towards third‐generation Sikuli ones. In this work, we extend Pesto to manage Web elements having (1) complex visual interactions and (2) multiple visual appearances. Pesto relies on aspect‐oriented programming, computer vision, and code transformations. Our new improved tool has been evaluated on two Web test suites developed by an independent tester. Experimental results show that Pesto manages and transforms correctly test suites with Web elements having complex visual interactions and multistate elements. By using Pesto, the migration of existing DOM–based test suites to the visual approach requires a low manual effort, since our approach proved to be very accurate.

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“…This paper proposes an automated method to evaluate the usability of a web site using machine-learning techniques. Harty stated that automated usability testing could uncover many types of issues if combinations of several techniques are used [3]. The proposed method is not supposed to be used as the only measure of usability of a website, but should be able to uncover usability issues related to the organization of the pages (information architecture), and can be used in combination with other types of usability testing techniques.…”

Section: Introductionmentioning

confidence: 99%

Method of neuro-fuzzy estimation of graphical user interface usability

Korviakov¹

2016

HoBMSTU.SIE

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User satisfaction on web sites depends on many factors and usability is one of these factors. A web site should be organized in a logical manner to aid the user in accomplishing their goal. This paper proposes an automated method for usability testing of a web site using machine-learning techniques to uncover usability issues related to the organization of the pages (information architecture). The information architecture was represented as a weighted directed graph. The graph features are used to train several machine learning models that can then be used to predict the usability score of another website. Models evaluated include classifiers of support vector, random forest, decision tree, regression models, etc. A number of machine learning models are evaluated to determine the best possible model for this specific use case, using 10-fold cross validation on various sized datasets. We also demonstrate a way of extracting a ranked list of prominent features to that can be improved.1

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Finding usability bugs with automated tests

Abstract: Automated usability tests can be valuable companions to in-person tests.

Cited by 28 publications

References 0 publications

Cultural differences in online beer marketing: findings from automated attention analysis

Cultural differences in online beer marketing: findings from automated attention analysis

Pesto: Automated migration of DOM‐based Web tests towards the visual approach

Method of neuro-fuzzy estimation of graphical user interface usability

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