Tag: disabilities

  • 92% of Devs Use AI, Survey Says ¦ Intel One Mono Font

    92% of Devs Use AI, Survey Says ¦ Intel One Mono Font

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: GitHub touts unbelievable AI stats, and Intel’s beautiful open source typeface. (more…)

  • GitHub Adds Accessibility Improvements for Developers With Disabilities

    GitHub Adds Accessibility Improvements for Developers With Disabilities

    GitHub today revealed it added several capabilities to make it easier for developers with disabilities to access its code repository platform. The new capabilities were announced to coincide with Global Accessibility Awareness Day.

    Capabilities highlighted include a navigation tool and a search tool that can be used with a screen reader that GitHub provides.

    In addition, GitHub’s contribution graph has been updated to remove barriers for keyboard-only and screen reader users.

    Finally, GitHub has made site-wide color contrast improvements to the light and dark themes presented by Primer, the GitHub Design System.

    Ed Summers, head of accessibility for GitHub, said there are more than 1.3 billion individuals with a wide variety of disabilities that could, with access to the right tools, write code. That community today, however, is underrepresented as a percentage of the larger IT community, he noted.

    However, as tools such as GitHub Copilot—a generative artificial intelligence (AI) tool that helps developers write better, more secure code—is paired with GitHub Copilot Voice—a speech interface for GitHub Copilot that is available in technical preview—the GitHub platform becomes more accessible to developers with disabilities, he said.

    Generative AI coupled with a speech interface that eliminates the need for a keyboard is lowering the barrier for entry for every potential developer. But for individuals with disabilities, it represents a tremendous advance, noted Summers. Anyone who understands how code should be constructed can build an application, he added.

    It’s not clear what impact generative AI will have on the global shortage of developer talent that has persisted for decades but it’s clear the pace at which applications can be developed is about to dramatically increase. In addition, many organizations have embraced working from home in the wake of the COVID-19 pandemic. That shift makes it easier for many individuals with disabilities to become part of the workforce because they no longer need to commute to an office.

    Generative AI platforms are fundamentally changing the way humans interact with machines. Instead of requiring a developer to create a level of abstraction to communicate with a machine, it’s now possible for machines to understand the language humans use to communicate with each other. Via a natural language interface, developers will soon be asking generative AI platforms to not only surface suggestions but also debug applications and write the code used to create an application.

    At this point, like it or not, the generative AI genie is out of the proverbial bottle. Just about every job function imaginable will be impacted to varying degrees. In the case of DevOps teams, the ultimate impact should involve less drudgery as many of the manual tasks that conspire to make managing DevOps workflows tedious are eliminated.

    It may be a while before the impact of generative AI is fully appreciated, and there will certainly be more advances to come that will be applicable to individuals with disabilities. In the meantime, however, many members of a DevOps team may not even realize a member of the team has a disability as the writing of code continues to be increasingly automated.

  • Three Manual Accessibility Testing Pain Points

    Three Manual Accessibility Testing Pain Points

    According to industry research, the vast majority of IT leaders view test automation as the single most important factor in accelerating software innovation. This also applies to automated accessibility testing – a great first step for making websites accessible to persons with disabilities. The new breed of automated tools can catch nearly 83% of all accessibility issues (not to be confused with overlays, which claim 100% automatic compliance.)

    Automation does not, however, replace the need for manual testing, which is the only surefire way to ensure all users can access the information on your website without difficulty. To get complete coverage, you also need to perform manual accessibility testing (which requires a human to complete using the various assistive technologies that people with disabilities depend on) with multiple browsers and interfaces. However, manual testing comes with several challenges, which is why testers often perceive it as painful or complicated.

    Pain Point One – WCAG Has Many Success Criteria

    The most widely-accepted set of accessibility standards are the Web Content Accessibility Guidelines (WCAG), created by the W3C. WCAG criteria are classified by various versions and levels. Versions include WCAG 1.0, 2.0, and most recently 2.1, with version 3.0 actively under development. Success criteria under each of these versions are further broken down into conformance levels A, AA and AAA, with each level adding criteria.

    Depending on which WCAG conformance level you choose, you could reasonably expect to check somewhere between 25 to 50 success criteria when assessing the accessibility of your site or app. As you can see, a significant amount of familiarity and expertise is required with WCAG success criteria to be able to perform accurate, full-coverage accessibility testing on a site or app.

    Fortunately, software has reached the point in testing maturity where there are guided instructions for testing for specific criteria that must be manually tested. One example is keyboard navigation, often used by persons with motor disabilities. In this instance, the tool would simulate a user who interacts with a web page solely by using their keyboard; then the tool would describe a step-by-step instruction to identify accessibility issues during keyboard navigation. One such example: a news site with a carousel featuring five news stories, only one of which is visible at a time. There needs to be ‘previous’ and ‘next’ buttons that can be accessed and triggered using a keyboard so that keyboard users can navigate through the stories just as easily as they could with a mouse.

    Pain Point Two – Screen Readers Take Time and Expertise to Learn

    In addition to understanding numerous success criteria, accessibility testers also need to understand how to use a screen reader, a popular form of assistive technology. There are numerous screen readers available including JAWS, NVDA, VoiceOver and Talkback. Now, imagine having to memorize more than 50 success criteria that need to be tested across three different screen readers in multiple testing environments (desktop, responsive web, native mobile, etc.).

    Luckily, customized testing methodologies have been developed based on a chosen ruleset and testing environment. This reduces the amount of memorization and prior experience the tester needs to run effective tests. With specific screen reader testing steps outlined for each ruleset and testing environment, accessibility teams can improve their efficiency and create a standardized testing process for the whole testing team to follow—whether they are screen reader experts or not—resulting in a significant productivity boost.

    Pain Point Three – WCAG Success Criteria Can Be Open to Interpretation

    Some WCAG success criteria can be very contextual. Criteria that appear simple to test for, like color contrast requirements, can sometimes be tricky to analyze. For example, imagine a black, bold-faced word featuring dark gray shadowing against a light gray website background.

    In this image, which two colors should be compared to verify whether the minimum color contrast requirements are satisfied? Light gray and black, dark gray and black or light gray and dark gray?

    In scenarios like this, different accessibility experts can (and will) have different opinions. For a developer, there is nothing more frustrating than receiving different remediation requirements for the same issue. This can create confusion and introduce significant delays in the release of a product.

    The solution is clearly documented and detailed requirements to help reduce the potential number of issues that can be interpreted differently. Properly documented testing processes can help ensure that the results coming from an accessibility test team will be consistent, and significant time will be saved communicating issues back and forth between testers and developers.

    Automated testing is great for addressing many ‘low-hanging fruit’ problems without having to be an accessibility expert or hire one, but it does not eradicate the need for manual testing. While there are certain characteristics of manual testing that can make it onerous, fortunately, there are guided testing tools, auditors, methodologies and more available to take the pressure off accessibility teams. This will enable development teams to strike the ideal composition of manual and automated accessibility testing that helps them identify and repair the highest possible number of issues.