skip to main content
research-article

Flexible Automatic Support for Web Accessibility Validation

Published:18 June 2020Publication History
Skip Abstract Section

Abstract

Automatic support for web accessibility validation needs to evolve for several reasons. The increasingly recognised importance of accessibility implies that various stakeholders, with different expertise, look at it from different viewpoints and have different requirements regarding the types of outputs they expect. The technologies used to support Web application access are evolving along with the associated accessibility guidelines. We present a novel tool that aims to provide flexible and open support for addressing such issues. We describe the design of its main features, including support for recent guidelines and tailored results presentations, and report on first technical and empirical validations that have provided positive feedback.

References

  1. Abascal, J., Arrue, M., & Valencia, X. (2019). Tools for web accessibility evaluation. Web Accessibility (pp. 479--503). London: Springer.Google ScholarGoogle Scholar
  2. Abduganiev, S. G. (2017). Towards automated web accessibility evaluation: a comparative study. Int. J. Inform. Technol. Comput. Sci, 9(9), 18--44.Google ScholarGoogle ScholarCross RefCross Ref
  3. Arrue, M., Vigo, M., & Abascal, J. (2008). Including heterogeneous Web accessibility guidelines in the development process. IFIP International Conference on Engineering for Human-Computer Interaction (pp. 620--637). Berlin: Springer.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Ballantyne, M., Jha, A., Jacobsen, A., Hawker, J. S., & El-Glaly, Y. N. (2018). Study of Accessibility Guidelines of Mobile Applications. 17th International Conference on Mobile and Ubiquitous Multimedia (pp. 305--315). ACM.Google ScholarGoogle Scholar
  5. Beirekdar, A., Vanderdonckt, J., & Noirhomme-Fraiture, M. (2002). Kwaresmi--Knowledge-based Web Automated Evaluation with REconfigurable guidelineS optiMIzation. (Springer, Ed.) DSV-IS, 2545, 362--376.Google ScholarGoogle Scholar
  6. Beirekdar A., Keita M., Noirhomme M., Randolet F., Vanderdonckt J., Mariage C. (2005) Flexible Reporting for Automated Usability and Accessibility Evaluation of Web Sites. In: Costabile M.F., Paternò F. (eds) Human-Computer Interaction - INTERACT 2005. INTERACT 2005. Lecture Notes in Computer Science, vol 3585. Springer, Berlin, HeidelbergGoogle ScholarGoogle Scholar
  7. Brajnik, G. (2004). Comparing accessibility evaluation tools: a method for tool effectiveness. Universal access in the information society, 3(3--4), 252--263.Google ScholarGoogle Scholar
  8. Brajnik, G., & Vigo, M. (2019). Automatic Web Accessibility Metrics. Where we were and where we went. (Springer, Ed.) Web Accessibility, 505--521.Google ScholarGoogle Scholar
  9. Consortium, W. W. (2018). Web content accessibility guidelines (WCAG) 2.1. Retrieved from https://www.w3.org/TR/WCAG21/Google ScholarGoogle Scholar
  10. EU Commission. (2016, October 26). Directive (EU) 2016/2102 of the European Parliament and of the Council. Retrieved from https://eur-lex.europa.eu: https://eur-lex.europa.eu/eli/dir/2016/2102/ojGoogle ScholarGoogle Scholar
  11. Fernandes, N., Kaklanis, N., Votis, K., Tzovaras, D., & Carriço, L. (2014). An analysis of personalized web accessibility. Proceedings of the 11th Web for All Conference (p. 19). ACM.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Fuertes, J. L., González, R., Gutiérrez, E., & Martínez, L. (2009). Hera-FFX: a Firefox add-on for semi-automatic web accessibility evaluation. Proceedings of the 2009 International Cross-Disciplinary Conference on Web Accessibililty (W4A) (pp. 26--35). ACM.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Gay, G., & Li, C. Q. (2010). AChecker: open, interactive, customizable, web accessibility checking. Proceedings of the 2010 International Cross Disciplinary Conference on Web Accessibility (W4A) (p. 23). ACM.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Gulliksen, J., Von Axelson, H., Persson, H., & Göransson, H. (2010). Accessibility and public policy in Sweden. Interactions, 17(3), 26--29.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Ivory, M. Y., & Hearst, M. A. (2001, December). State of the Rt in Automating Usability Evaluation of User Interfaces. ACM Computing Surveys, 33(4), 470--516.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Lazar, J., & Olalere, A. (2011). Investigation of best practices for maintaining section 508 Compliance in US federal web sites. International Conference on Universal Access in Human-Computer Interaction (pp. 498--506). Berlin: Springer.Google ScholarGoogle Scholar
  17. Aliaksei Miniukovich, Michele Scaltritti, Simone Sulpizio, and Antonella De Angeli. 2019. Guideline-Based Evaluation of Web Readability. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). Association for Computing Machinery, New York, NY, USA, Paper 508, 1--12. DOI:https://doi.org/10.1145/3290605.3300738Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Mirri, S., Muratori, L. A., & Salomoni, P. (2011). Monitoring accessibility: large scale evaluations at a geo political level. The proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility (pp. 163--170). New York: ACM.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Lourdes Moreno, Rodrigo Alarcon, Isabel Segura-Bedmar, and Paloma Martínez. 2019. Lexical simplification approach to support the accessibility guidelines. In Proceedings of the XX International Conference on Human Computer Interaction (Interaccion '19). Association for Computing Machinery, New York, NY, USA, Article 14, 1--4. DOI:https://doi.org/10.1145/3335595.3335651Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Mucha, J., Snaprud, M., & Nietzio, A. (2016). Web page clustering for more efficient website accessibility evaluations. International Conference on Computers Helping People with Special Needs (pp. 259--266). Springer.Google ScholarGoogle ScholarCross RefCross Ref
  21. Jacob Nielsen, Success Rate: The Simplest Usability Metric, https://www.nngroup.com/articles/success-rate-the-simplest-usability-metric/Google ScholarGoogle Scholar
  22. Nietzio, A., Eibegger, M., Goodwin, M., & Snaprud, M. (2011). Towards a score function for WCAG 2.0 benchmarking. Proceedings of W3C Online Symposium on Website Accessibility Metrics. Retrieved from https://www.w3.org/WAI/RD/2011/metrics/paper11Google ScholarGoogle Scholar
  23. Paternò, F., & Schiavone, A. G. (2015). The role of tool support in public policies and accessibility. Interactions, 22(3), 60--63.Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Power, C., Freire, A., Petrie, H., & Swallow, D. (2012). Guidelines are only half of the story: accessibility problems encountered by blind users on the web. Proceedings of the SIGCHI conference on human factors in computing systems (pp. 433--442). ACM.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Schiavone, A. G., & Paternò, F. (2015). An extensible environment for guideline-based accessibility evaluation of dynamic Web applications. Universal access in the information society, 14(1), 111--132.Google ScholarGoogle Scholar

Index Terms

  1. Flexible Automatic Support for Web Accessibility Validation

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader
      About Cookies On This Site

      We use cookies to ensure that we give you the best experience on our website.

      Learn more

      Got it!