dequelabs/axe-core

Features

• Accessibility Testing - Provides a programmatic engine for automating accessibility testing within CI/CD pipelines and UI test suites.
• UI Accessibility Scanning - Scans web pages and interface code to detect accessibility violations and generate detailed remediation reports.
• Accessibility Linting - Performs static analysis on source code to identify accessibility barriers before the code is compiled.
• Compliance Gating - Integrates accessibility checks into CI/CD pipelines to prevent code with accessibility violations from being merged.
• Accessibility Linters - Provides a programmatic linter that detects accessibility violations in real time within code editors and CI/CD pipelines.
• Accessibility - Executes automated accessibility tests from the CLI to validate complex user flows and responsive layouts.
• CI/CD Integrations - Executes automated accessibility checks via command-line tools and GitHub Actions within CI/CD pipelines.
• IDE Accessibility Linters - Provides real-time accessibility linting directly within code editors to catch violations during the authoring process.
• CI/CD Pipeline Integrations - Automates accessibility auditing within deployment pipelines to prevent the release of non-compliant code.
• CI CD Pipelines - Triggers automated accessibility audits during pull requests to prevent regressions in the codebase.
• Just-in-Time Access - Marks accessibility violations directly in the editor to ensure immediate correction of patterns that block users.
• GitHub Actions - Uses GitHub Actions to automatically trigger accessibility checks upon the creation of pull requests.
• Rule Execution Engines - Implements a rule execution engine that validates the current browser DOM against accessibility standards.
• Accessibility Data Aggregators - Aggregates accessibility scan data from multiple platforms into a centralized monitoring dashboard.
• Accessibility Regression Tracking - Links accessibility results to Git commits to evaluate the impact of changes and monitor project health.
• Accessibility Compliance Verifiers - Aggregates scan results and links accessibility violations to version control to track remediation progress over time.
• Accessibility Scan Reports - Generates detailed reports and diagnostic data resulting from automated accessibility scans.
• Guided Testing Workflows - Walks users through complex testing scenarios with step-by-step instructions to ensure compliance.
• Accessibility Auditing - Verifies that web interfaces comply with industry accessibility standards and semantic HTML requirements.
• Browser-Based Accessibility Auditing - Scans web pages for accessibility defects directly through the browser's developer tools.
• Mobile Accessibility Auditing - Analyzes user interfaces built with various mobile frameworks to identify accessibility violations across platforms.
• Accessibility Auditors - Programmatically inspects web and mobile interfaces to verify compliance with accessibility guidelines and success criteria.
• Accessibility Scanners - Ships a programmatic scanner that integrates into end-to-end test suites to find interface barriers across browsers.
• iOS - Analyzes iOS applications on physical devices or emulators to detect accessibility violations.
• Accessibility Integrations - Wraps end-to-end test methods to automatically validate web pages for accessibility violations with minimal code changes.
• CLI Test Runners - Provides a command-line interface to script page loads and user interactions for automated accessibility testing.
• Accessibility Pipeline Integrations - Integrates accessibility auditing into CI/CD pipelines, GitHub Actions, or Git pre-commit hooks to block defects before they reach production.
• Accessibility Remediation Tools - Produces AI-powered instructions and code fixes to resolve identified accessibility compliance issues.
• Image Content Analyzers - Analyzes image content using AI to identify missing alternative text and flag informative images.
• Web-Based Computer Vision - Employs web-based computer vision to identify accessibility barriers like missing semantic headings from visual appearance.
• Vision Analysis - Uses vision analysis to detect visual headings and color contrast issues that are not visible in the DOM.
• AI Integration - Integrates artificial intelligence to enhance accessibility detection and manage AI data sharing preferences.
• Collaboration and Sharing - Distributes accessibility test records and issue groups among collaborators to coordinate remediation.
• Issue Tracking - Centralizes results from automated test runs and scans to track and resolve accessibility violations.
• Regression Tracking - Associates accessibility violations with version control commit hashes to monitor regressions and track remediation.
• Jira Connectors - Integrates with Jira to export accessibility violations as trackable issues for development teams.
• Analysis Result Exporters - Outputs accessibility test results using a standardized JSON schema for interoperability between auditing tools.
• Scan Data Importers - Connects automated scanning projects to a reporting system to import and centralize accessibility information.
• CLI Accessibility Auditors - Sends local files to a linting engine using a CLI tool to automate accessibility checks outside of a browser.
• IDE Extensions - Provides plugins for code editors to detect accessibility violations in real time during development.
• Accessibility Linter Plugins - Offers specialized plugins for code editors to perform real-time accessibility rule checking.
• IDE Real-time Feedback - Provides immediate accessibility analysis and remediation guidance directly within the code editor during development.
• Real-Time Code Diagnostics - Alerts developers to accessibility issues within the code editor as they write source code.
• Standardized Accessibility Exports - Generates a consistent JSON output format for accessibility violations to ensure compatibility across auditing tools.
• Analysis Result Exporters - Outputs accessibility violation summaries and detailed rule failures in a standardized JSON format for external integration.
• Quality Gates - Integrates accessibility checks into CI/CD pipelines to prevent code containing accessibility violations from being merged into a project.
• Accessibility Result Synchronization - Send page state and commit-linked data to a centralized hub to track trends and remove duplicate entries.
• Version Control Integration - Associates accessibility failures with specific Git commits to pinpoint when violations were introduced.
• Accessibility Training - Provides role-based overviews and deep-dive technical courses to teach accessibility standards and inclusive design.
• Accessibility Analysis Libraries - Analyzes React Native code to detect accessibility violations early in the development cycle.
• Assessment Progress Monitoring - Monitors the completion status of accessibility test runs across defined pages to ensure all checkpoints are verified.
• Role Mappings - Maps proprietary custom element tags to standard accessibility roles to validate non-standard interface components.
• CI/CD Integrations - Runs accessibility audits via command-line tools, GitHub Actions, or pre-commit hooks to block problematic code from being merged or deployed.
• Accessibility Trend Analysis - Links test results to Git commits to monitor accessibility progress and evaluate the impact of code changes.
• Team Collaboration Tools - Facilitates the distribution of detected accessibility violations among team members for collaborative fixing.
• Rule Suppression Comments - Supports the use of inline code comments to suppress specific accessibility linting rules for targeted blocks.
• Analysis Result Exports - Exports accessibility analysis findings into various portable formats for reporting and tracking.
• Audit Result Tracking - Provides historical tracking of accessibility audit results linked to specific project versions.
• Test Performance Monitors - Tracks execution metrics and accessibility performance data over time to measure project progress.
• Accessibility Auditing Tools - Uses command-line tools and plugins to detect accessibility violations during the development cycle.
• AI-Powered Analysis - Leverages machine learning to automatically detect element roles and review color contrast.
• Guided Evaluations - Walks non-experts through specific testing procedures to identify accessibility violations without specialized knowledge.
• Heuristic Violation Detection - Employs computer vision and language models to find complex accessibility issues that rule-based testing misses.
• ML-Driven Test Automation - Uses machine learning to process screenshots and automate manual steps within guided accessibility tests.
• Automated Test Suites - Allows the injection of accessibility scans into existing automated test suites, mapping failures to specific code contexts.
• Accessibility Test Integrations - Integrates accessibility checks into existing automated UI tests to capture failures with Git context and centralized reporting.
• Browser Automation - Integrates with browser automation tools to execute accessibility audits during simulated user interactions.
• User Interaction Simulation - Executes browser actions such as form filling or banner dismissal to prepare the page state for accessibility scanning.
• Accessibility Reviews - Uses machine learning to identify input labels and analyze element roles to streamline the review process.
• Test Report Exporters - Serializes accessibility audit outcomes into various standardized reporting formats for external documentation.
• Test Result Reporters - Generates formatted reports of accessibility test execution outcomes for analysis.
• Result Sharing - Provides mechanisms to share specific accessibility test results and issue groups with other team members.
• Browser Automation Testing - Orchestrates testing activity across browsers to ensure consistent accessibility evaluations across different environments.
• Visual Analysis Optimizations - Processes page screenshots through machine learning to automate complex accessibility checks and improve testing accuracy.
• Manual Testing Procedures - Walks users through documented workflows for verifying accessibility requirements that cannot be detected by automated scans.
• Test Data Management - Stores and manages test cases, runs, and identified accessibility issues to track remediation progress.
• Test Execution Reports - Maintains long-term records of accessibility execution runs and violations for reporting and auditing.
• Visual Markup Analysis - Identifies headings based on visual appearance to find elements that lack correct semantic markup.
• Manual Testing Guides - Provides detailed instructions for verifying specific accessibility checkpoints and logging issues discovered during manual review.
• Contrast Validators - Calculates luminance ratios and uses screenshots to verify that text meets contrast requirements.
• Automatic Contrast Adjusters - Identifies and automatically fixes color contrast violations to meet accessibility standards.
• Accessibility Rule Mapping - Maps proprietary component properties to standard attributes to validate custom elements against accessibility rules.
• Custom Component Auditing - Scans custom interface elements for accessibility defects using plugins to ensure consistency.
• Semantic Heading Validation - Compares computer vision analysis with page source to find text that looks like a heading but lacks semantic markup.
• Focus State Indicators - Analyzes focusable elements to ensure visual styles change when focused for keyboard accessibility.
• Dynamic State Analysis - Detects DOM changes during execution and re-analyzes the page to verify that dynamic content remains accessible.
• Test-Frameworks - Accessibility engine for automated web UI testing.

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