dequelabs/axe-core

Accessibility engine for automated Web UI testing

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Summary Information

Updated 48 minutes ago
Added to GitGenius on September 8th, 2026
Created on June 10th, 2015
Open Issues & Pull Requests: 441 (+0)
GitHub issues: Enabled
Number of forks: 927
Total Stargazers: 7,492 (+0)
Total Subscribers: 173 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 25.7 hours
Mean response time: 69.2 days
90th percentile: 80.3 days
Tracked items: 444

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 99% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "ungroomed" is answered fastest, typically in about 12 hours, while "support" waits about 2 weeks. 35% of tracked open issues have had no activity in three months. Only 4% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 260
New in 7 days: 6
Closed in 7 days: 3
Avg open age: 780 days
Stale 30+ days: 180
Stale 90+ days: 68

Recent activity

Opened in 7 days: 4
Closed in 7 days: 1
Comments in 7 days: 5
Events in 7 days: 14

Top labels

  • fix (142)
  • rules (98)
  • feat (90)
  • ungroomed (67)
  • info needed (59)
  • support (44)
  • standards (43)
  • QA: Passed (41)

Detailed Description

axe-core is an accessibility testing engine for automated Web UI testing that integrates into existing test environments and development workflows.

The tool addresses the problem that most accessibility testing happens too late in development, after a product is feature-complete. axe-core solves this by embedding accessibility checks directly into unit tests, integration tests, and browser tests alongside functional testing. It works by scanning HTML-based interfaces against rules derived from WCAG 2.0, 2.1, and 2.2 at levels A, AA, and AAA, plus best practice checks. The engine can automatically detect which rules apply to the evaluation context and supports testing across iframes of any depth.

Teams should adopt this tool if they want to catch accessibility problems early in development rather than at the end. It suits projects using modern browsers and any testing framework or environment, since it integrates with existing test suites rather than requiring separate tooling. The tool is designed to return zero false positives and works with in-memory fixtures, static fixtures, and integration tests. For teams wanting to extend coverage beyond automated detection, the README recommends pairing it with the axe-linter VSCode extension for real-time feedback during coding and the axe browser extension for guided manual testing.

Development on the project shows consistent activity with regular updates to rule coverage and bug fixes. The maintainers actively expand support for newer WCAG versions and accessibility standards. The tool receives ongoing maintenance and improvements to its detection accuracy and integration capabilities.