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On Web Accessibility
Evaluation Environments
                    W4A 2011


   Nádia Fernandes, Rui Lopes, Luís Carriço
       {nadia.fernandes,rlopes,lmc}@di.fc.ul.pt
Introduction

• Modern Web development transcends
  static HTML
• Evaluation tools (typically) stay outside the
  browser
• Goal: to study the impact of evaluating
  accessibility in the browser
Web Browsing
• Web page, first HTTP response
• Resources, ancillary
  transformations (CSS, Javascript)

• AJAX, browsing-time
  transformations
Hypothesis
 Evaluating Web content in the browser provides more
accurate and more in-depth analysis of its accessibility.

   • Need for understanding the differences and
      limitations of evaluation environments
   • Evaluation process (i.e., its implementation)
      must be the same in both environments, for
      comparison purposes
Web
Accessibility
Evaluation
Environments
Implementation
• Javascript, same techniques (18) in both environments
• Results transformed into EARL & CSV
• Execution in each environment at respective timings:

          Command line,              Browser,
          after HTTP GET            bookmarklet
Testability & Validation
• Testbed with 102
  HTML documents
• Implementation
  returns the same
  results in both
  environments, for the
  same HTML document
Experimental Study


• Analysis of evaluation results in both
  environments
• 82 homepages from Alexa Top 100 Web sites
Data Acquisition and Processing

 • Time between HTTP GETs, 89.72s               (σ ≈ 70s)


 • Document size average:
    •   Command line, 70KB (σ ≈ 95KB)

    •   Browser, 81KB (σ ≈ 127KB)


 • Document HTML element count average:
    •   Command line, 915 elements (σ ≈ 95KB)

    •   Browser, 1154 elements (σ ≈ 95KB)
The differences of an HTML
document in both environments was
   observed, and is significative.
Results: Average Outcomes
     Successes
 •   Command line, 9.67 elements (σ ≈ 19.12)

 •   Browser, 272.78 elements (σ ≈ 297.10)


     Failures
 •   Command line, 47.44 elements (σ ≈ 70.82)

 •   Browser, 90.10 elements (σ ≈ 125.93)


     Warnings
 •   Command line, 425.02 elements (σ ≈ 682.53)

 •   Browser, 685.21 elements (σ ≈ 1078.10)
Results: Incorrect Outcomes
• False positives and
  false negatives were
  found in Command
  line evaluation
  applicability
• 67% of the criteria
  yielded false
  negatives
Results: Criterion 1.1.1
• Availability of alternative text content
• We detected a high increase of scripted
  image injection
Results: Other Criteria

Criterion 1.2.3 (Media alternatives)
Almost all occurrences in the browser




Criterion 2.4.4 (Link purpose)
One case of false positives detection




Criterion 3.2.2 (On submit buttons)
Some cases where buttons were injected
Conclusions
• Accessibility evaluation study of 82
  homepages from Alexa Top 100 Web sites
• Compare evaluation environments
• Scripts alter Web pages in a significant way
• Accessibility evaluation is affected, both on
  incorrect and incomplete results in Command
  line environment
Limitations
• Possibility of artifacts introduced between
  requests for same Web page
• Analysis of HTML DOM tree
• Impossibility to check if a given individual
  result occurs in both environments
• Automated evaluation yields limited results
Ongoing Work

• Implementation of post-cascading and post-
  content flow CSS-aware techniques
• Continuous monitoring of DOM
  manipulation (to, e.g., detect live regions)
• Detection of differences between DOM
  trees, to pinpoint results
Thank you
rlopes@di.fc.ul.pt

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On Web Accessibility Environments

  • 1. On Web Accessibility Evaluation Environments W4A 2011 Nádia Fernandes, Rui Lopes, Luís Carriço {nadia.fernandes,rlopes,lmc}@di.fc.ul.pt
  • 2. Introduction • Modern Web development transcends static HTML • Evaluation tools (typically) stay outside the browser • Goal: to study the impact of evaluating accessibility in the browser
  • 3. Web Browsing • Web page, first HTTP response • Resources, ancillary transformations (CSS, Javascript) • AJAX, browsing-time transformations
  • 4. Hypothesis Evaluating Web content in the browser provides more accurate and more in-depth analysis of its accessibility. • Need for understanding the differences and limitations of evaluation environments • Evaluation process (i.e., its implementation) must be the same in both environments, for comparison purposes
  • 6. Implementation • Javascript, same techniques (18) in both environments • Results transformed into EARL & CSV • Execution in each environment at respective timings: Command line, Browser, after HTTP GET bookmarklet
  • 7. Testability & Validation • Testbed with 102 HTML documents • Implementation returns the same results in both environments, for the same HTML document
  • 8. Experimental Study • Analysis of evaluation results in both environments • 82 homepages from Alexa Top 100 Web sites
  • 9. Data Acquisition and Processing • Time between HTTP GETs, 89.72s (σ ≈ 70s) • Document size average: • Command line, 70KB (σ ≈ 95KB) • Browser, 81KB (σ ≈ 127KB) • Document HTML element count average: • Command line, 915 elements (σ ≈ 95KB) • Browser, 1154 elements (σ ≈ 95KB)
  • 10. The differences of an HTML document in both environments was observed, and is significative.
  • 11. Results: Average Outcomes Successes • Command line, 9.67 elements (σ ≈ 19.12) • Browser, 272.78 elements (σ ≈ 297.10) Failures • Command line, 47.44 elements (σ ≈ 70.82) • Browser, 90.10 elements (σ ≈ 125.93) Warnings • Command line, 425.02 elements (σ ≈ 682.53) • Browser, 685.21 elements (σ ≈ 1078.10)
  • 12. Results: Incorrect Outcomes • False positives and false negatives were found in Command line evaluation applicability • 67% of the criteria yielded false negatives
  • 13. Results: Criterion 1.1.1 • Availability of alternative text content • We detected a high increase of scripted image injection
  • 14. Results: Other Criteria Criterion 1.2.3 (Media alternatives) Almost all occurrences in the browser Criterion 2.4.4 (Link purpose) One case of false positives detection Criterion 3.2.2 (On submit buttons) Some cases where buttons were injected
  • 15. Conclusions • Accessibility evaluation study of 82 homepages from Alexa Top 100 Web sites • Compare evaluation environments • Scripts alter Web pages in a significant way • Accessibility evaluation is affected, both on incorrect and incomplete results in Command line environment
  • 16. Limitations • Possibility of artifacts introduced between requests for same Web page • Analysis of HTML DOM tree • Impossibility to check if a given individual result occurs in both environments • Automated evaluation yields limited results
  • 17. Ongoing Work • Implementation of post-cascading and post- content flow CSS-aware techniques • Continuous monitoring of DOM manipulation (to, e.g., detect live regions) • Detection of differences between DOM trees, to pinpoint results

Editor's Notes

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