Note: The creation of this article on testing Name, Role, Value was human-based, with the assistance on artificial intelligence.
Explanation of the success criteria
WCAG 4.1.2 Name, Role, Value is a Level A conformance level Success Criterion. It sits at the heart of accessibility for assistive technologies, ensuring that all interactive components are both perceivable and operable through programmatic means. This criterion requires that every user interface component, such as buttons, links, form fields, and custom widgets, clearly communicates its name (what it is called), role (what it does), and value (its current state or setting) to assistive technologies like screen readers. In essence, it guarantees that users who rely on these technologies receive the same information and control as sighted or non-disabled users.
Meeting 4.1.2 is not just a technical exercise; it’s a cornerstone of inclusive design. It pushes developers to implement semantic HTML, leverage ARIA roles and attributes responsibly, and validate that dynamic content updates are announced correctly. When Name, Role, and Value are handled correctly, digital experiences become reliably interpretable, empowering all users to navigate, understand, and act with confidence across complex web applications and modern interfaces.
Who does this benefit?
- Screen reader users rely on accurate names, roles, and values to understand and navigate interactive elements that sighted users perceive visually.
- Keyboard-only users benefit when controls correctly expose their purpose and state, ensuring consistent focus and operability without a mouse.
- Users of voice control software depend on meaningful element names to issue clear voice commands that match what’s programmatically available.
- Users with cognitive disabilities gain confidence and predictability when controls behave consistently across assistive technologies.
Testing via Automated testing
Automated testing offers speed and scalability, making it ideal for scanning large codebases to identify missing labels, improper ARIA roles, or invalid markup structures. It efficiently flags obvious violations, such as buttons without discernible names or elements misusing ARIA attributes. However, automated tools only validate what is explicitly detectable in the code, they cannot judge whether a label is meaningful, a role is appropriate for its function, or if dynamic updates are announced to assistive technology as intended. This creates a risk of false confidence: a site may appear compliant in reports yet still fail users in practice.
Testing via Artificial Intelligence (AI)
AI-based testing adds intelligence to the process by attempting to infer intent, context, and relationships that automation alone misses. Using machine learning and pattern recognition, AI can identify unlabeled elements likely meant to be interactive or suggest appropriate ARIA roles based on visual or functional patterns. It can even simulate aspects of screen reader behavior to predict user experience issues. Still, AI remains an assistant, not an arbiter, it cannot yet fully understand business logic, user expectations, or contextual meaning, and it occasionally produces false positives when its predictions don’t align with human design intent.
Testing via Manual testing
Manual testing remains the gold standard for 4.1.2, as it engages human judgment, empathy, and expertise to interpret how assistive technologies truly perceive and announce Name, Role, and Value. Expert testers can verify whether ARIA attributes enhance or hinder accessibility, ensure dynamic updates are communicated in real time, and assess whether naming conventions are meaningful to users. The trade-off is that manual testing is resource-intensive and slower to scale, requiring specialized skill and assistive technology proficiency.
Which approach is best?
A hybrid approach to testing WCAG Success Criterion 4.1.2 Name, Role, Value combines the precision of automation, the intelligence of AI, and the discernment of human expertise to deliver the most reliable and actionable results. This integrated strategy recognizes that accessibility is not achieved through a single lens, it’s a balance between scalable detection, contextual interpretation, and experiential validation.
The process begins with automated testing, serving as the foundation for identifying structural and syntactic issues at scale. Automated tools efficiently scan the DOM for missing or invalid ARIA attributes, elements without accessible names, and role mismatches that compromise interoperability with assistive technologies. This phase provides rapid, repeatable feedback across vast codebases and accelerates early detection during development.
Next, AI-based testing builds on automation’s groundwork by interpreting context and intention. Using computer vision, pattern recognition, and behavioral modeling, AI tools can infer when interactive elements are visually designed as buttons but coded incorrectly, or when dynamic content updates fail to expose new values to screen readers. AI bridges the gap between raw code and human experience, flagging potential perception mismatches and suggesting likely fixes. It provides insight into how real users might experience the interface, something traditional rule-based tools cannot replicate.
Finally, manual testing ensures that what’s technically correct is also functionally accessible. Skilled accessibility professionals validate automated and AI findings, confirming that accessible names are meaningful, roles are appropriate for the element’s purpose, and dynamic state changes are communicated effectively through assistive technologies. Manual testing also evaluates the “why” behind the interface, whether the design’s intent aligns with user expectations and whether the experience feels seamless for screen reader and keyboard users alike.
In a mature accessibility program, these three methods operate in concert rather than isolation. Automation provides breadth, AI contributes depth and contextual intelligence, and manual testing delivers human-centered accuracy. Together, they form a continuous feedback loop that strengthens both compliance and usability. Organizations that adopt this hybrid strategy move beyond checkbox testing, they evolve into accessibility leaders who build experiences that communicate clearly, behave predictably, and include everyone with equal clarity and respect.
Related Resources
- Understanding Success Criterion 4.1.2 Name, Role, Value
- mind the WCAG automation gap
- Accessible Names and Labels: Understanding What Works and What Doesn’t
- Using markup features to expose the name and role, allow user-settable properties to be directly set, and provide notification of changes
- Using HTML form controls and links
- Using label elements to associate text labels with form controls
- Using the title attribute of the iframe element
- Using the title attribute to identify form controls when the label element cannot be used
- Using HTML according to spec
- Using aria-label to provide an accessible name where a visible label cannot be used
- Using aria-labelledby to provide a name for user interface controls
- Using the accessibility API features of a technology to expose names and … notification of changes
- Creating components using a technology that supports the accessibility … notification of changes
- Using a WAI-ARIA role to expose the role of a user interface component
- Using WAI-ARIA state and property attributes to expose the state of a user interface component
- Using aria-labelledby to provide a name for user interface controls
- Web Accessibility Initiative – Accessible Rich Internet Applications (ARIA)
- ARIA in HTML
- Accessible Name and Description Computation 1.2
- ARIA Authoring Practices Guide