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Author: Syed Hamid

  • Considering Scriptless Automation: iOS App Dev in 2023

    Considering Scriptless Automation: iOS App Dev in 2023

    According to Statista, over 31,000 apps were released on Apple’s App Store in March 2023. As impressive as that is, it’s considerably smaller than the number of apps submitted to the Apple store during the same month.

    And it’s probably less than the number of apps removed from the App Store.

    Why?

    According to Apple, most submissions fail because of common issues like bugs, crashes, incompleteness, placeholder data and broken links.

    But getting app approval is just one of many challenges faced by iOS developers today.

    Contemporary iOS App User Expectations

    The truth is, even if you slip by Apple, there’s an even greater critic to be concerned about: Your audience. Users are much less forgiving and have high expectations. If your app isn’t perfect, you’ll lose your chance at meaningful adoption and your users will just go elsewhere.

    For iOS users, perfect is simply the status quo, and users have grown to expect it. In practice, this means that apps must be stable across devices and versions, see regular improvements. and provide a great user experience at all times.

    Seamless experience between devices, versions and iterations
    iOS users expect the same experience across multiple devices. From one iPhone to the next, from version to version and from screen size to screen size. It’s the responsibility of developers to prioritize a consistent experience across devices.

    Fast release cycles and regular updates
    Contemporary app users demand feature-rich applications that go above and beyond the simple functions they expect from an app. Given the statistics above, chances are that the competition is fierce. Achieving success usually requires an efficient and speedy release cycle with more planning, more deployments and more testing.

    Easy and frictionless user experience
    User experience (UX) and functionality are one of the big reasons iOS adoption is so strong. People have come to expect high quality from anything under the Apple banner: Users expect an intuitive and trouble-free user experience on every app with which they interact. Every user’s experience needs to be intuitive, issue free and consistent with other iOS applications.

    Challenges Abound

    Meeting those escalating user expectations comes with a wide variety of challenges. For example:

    Device landscape fragmentation
    With so many device types and form factors in circulation, how do you test across all of them? With dozens of iterations of the iPhone combined with an array of versions, screen sizes and configurations, app developers need a way to test on enough devices to cover the majority of their user bases.

    This leads many developers to turn to simulators and emulators to cover devices they lack access to.

    This poses another problem. Simulators aren’t perfect. A simulator doesn’t replicate the functions of the actual device; it can only mimic certain aspects of an iOS device. And it simply can’t effectively mimic hardware, component functionality or network.

    Using a simulator, you can’t test how an application will respond to factors like low battery, a rising network spike, or limited memory, not to mention GPS and camera functionality. You also can’t monitor usage metrics or run meaningful performance tests.

    Real devices present their own challenge. The vast majority of the time, developers will have to worry about the cost of acquiring, storing, maintaining and updating devices. In addition, they’ll have to centralize and control access to them. In an increasingly remote workforce, it’s not a great strategy.

    Manual tests
    Today, most organizations are over-reliant on manual testing. The result? Running test cases becomes the bottleneck that holds up releases. Sure, manual testing is unavoidable in some cases, but their ad-hoc, inconsistent nature leaves room for error. No matter how detailed the instructions may be, people test differently, and that’s a disaster waiting to happen in today’s complex software world.

    Maintaining complex test scripts
    If you’re automating test cases, you’ve experienced the pain of maintaining code-based test scripts. Every release requires coinciding updates to countless unit tests, integration tests and UI tests. The smallest changes can break test cases, causing false negatives and more deployment delays.

    On top of that, you’ve also got to worry about retaining talent that understands your language-specific testing framework. Given the economic uncertainties of today, that’s certainly not a good situation to be in.

    Constant iOS updates
    Each year sees Apple deliver iOS major releases and a variety of minor releases, patches and bug fixes. Organizations have to test after two release cycles: Their own and Apple’s. Failure to do so can lead to compatibility and App Store compliance issues.

    App store guidelines
    As I mentioned above, Apple maintains strict guidelines for any apps published on the App Store. Excellent testing can mean the difference between releasing an app or waiting another few weeks for the next approval. When time is money, this adds up fast.

    Security at scale
    As requirements change, scope increases and features add up, it’s easy to see how it can become more and more challenging to monitor for potential security flaws. In turn, testing needs to be continually updated to reflect the latest security risks.

    A Shift Toward Scriptless Solutions

    Scriptless automation is part of a growing industry of no-code automation tools, often dubbed the no-code revolution. It’s everything test automation is without the reliance on code-based frameworks.

    Scriptless test automation involves recording user interactions with app elements, asserting expected outcomes and assessing the results. The test is then automated, templatized and extended to test other scenarios.

    With scriptless test automation, you can walk through test cases step by step. Some tools even allow you to test on live devices and choose from real iOS devices that are hosted in the cloud.

    Scriptless testing allows you to:

    ● Easily reuse and templatize test scripts. Scriptless automation makes it easier to reuse test cases, create templates and compose new test cases.

    ● Enable faster time to value. Write test cases quicker, make changes without knowing how to write code and integrate directly with your CI/CD tool. As soon as you make changes to your application, your testing team is right there. Some no-code testing tools can analyze your source code and identify testing gaps so that you can address them right away.

    ● Untangle the web of code-based dependencies. With scriptless iOS test automation, testers don’t have to lift and shift their code every time they make a big change. Instead, the no-code framework provides a visual, easily-navigated UI that tells you simply what’s passing, what’s failing and what needs to be updated.

    ● Improve collaboration between teams. Scriptless iOS test automation improves collaboration between testers and developers by making it easy for all teams to visualize test cases.

    Real Device Testing

    When the pain points of fragmentation meet the shortcomings of simulation, developers are wise to test on real devices. At the end of the day, live device testing is the only way to accurately capture an end user’s experience.

    Yet it’s no secret that managing your own device lab is expensive and unrealistic for modern remote work environments. A real device cloud setup solves this problem: A device cloud hosts devices for you that you can access from your desktop, from anywhere.

    Given the ever-increasing complications of today’s mobile app landscape and the incredibly cut-throat mobile app landscape, it’s worth keeping in mind that you may only get one chance at making the right impression on your audience. Getting testing right is the key.

    Into the Future

    Everyone expects more. As a competitive organization, you have to do more with less: Fewer resources, less time and less room for error. Scriptless automation and real device testing won’t guarantee that your app stands out from the crowd, but it will certainly help.

  • Let the Machines Do It: AI-Directed Mobile App Testing

    Let the Machines Do It: AI-Directed Mobile App Testing

    AI has been in the news a lot lately. We’ve all heard a lot about ChatGPT and you’ve no doubt encountered the end result of a variety of other advances in AI technology of late, such as Lensa. But there’s also a much quieter and less visible shift happening behind the scenes during the development of your favorite apps—AI-directed mobile app testing. Let’s take a look.

    Behind the Scenes

    It’s no secret that every product, no matter the industry, goes through a gauntlet of tests before it’s unleashed on the general public. This goes for everything from a simple object like a cardboard box, for example, to a far more complex product, such as the latest electric vehicle.

    The same goes for the mobile apps on your phone. And if you haven’t given that much thought, then good! It means that the QA team behind the app’s functionality did its job, producing a seamless experience that functioned without a hitch, exactly as you wanted and expected.

    But that’s not always the way it goes, and mobile app testing is only growing more complex. That’s a growing problem that AI will eventually resolve.

    If your app didn’t perform as expected, you—and many other users like you—may delete it and move on to the next app that promises to do the same thing. While this may not seem like a big deal to you as the user, it’s a total disaster for the tireless teams working behind the scenes to ensure a successful app launch or update.

    The adage ‘You only get one chance to make a first impression’ is very true in the mobile app market. It’s a big, crowded and cutthroat mobile app world out there, and users simply have no incentive to put up with an app that doesn’t do exactly what it’s supposed to do. After all, for every single app, there are often several others standing by to scoop up your unhappy (former) users.

    This issue is by no means restricted to small development teams strapped for resources. I’m sure you can think of some high-profile software releases from major companies that have launched in a disastrous state over the past few years (particularly in the tremendously profitable arena of video games).

    So why is it that some teams cut corners when it’s time for testing, only to dearly wish they hadn’t?

    Well, the answer is pretty simple: Up until very recently, mobile app testing has traditionally been time-consuming, complex and bewildering, all too frequently delaying releases and flabbergasting QA teams.

    To understand this ongoing problem, let’s take a look at what this kind of mobile app testing entails and how this landscape has recently started to shift, as well as what’s on the horizon to make it all more efficient.

    Cutting Corners = Consequences

    Once upon a time—in an era that seems like it was really just yesterday—software testing was performed manually, entirely by hand. This was possible because quality assurance personnel only needed to consider a very limited set of variables: There were only so many use cases and form factors to consider, and programs were only expected to do so much.

    It’s hard to imagine testing a modern app manually and having the result be effective. The approach is only reasonable under very limited circumstances. Nowadays, teams use automated tests, which save them a tremendous amount of time, effort and resources.

    Yet these automated tests come with their own problems. Most of these automated tests are hand-coded, meaning that they must be set up and adjusted by specialists with a background in computer programming. Such specialists are not only costly and in demand, but they’re also needed for later aspects of the software development cycle, such as developing new product features and overseeing other aspects of production.

    And this is where companies start to cut corners and miss problems and issues, both large and small. Instead of what is known as shifting left (that is, testing as early in the cycle as possible), many teams, unfortunately, view testing as a burden or afterthought. Only when things go haywire and they have a full-blown crisis on their hands does the need for rigorous app testing become apparent.

    Testing, Machine-Made

    This is where machine learning and artificial intelligence enter the picture. For several years, we’ve known that testing performed by machines will be more and more necessary to handle increasingly complex apps, and it won’t be long before the cost associated with the complex testing scenarios will simply become too much for many developers.

    Fortunately, advances continue to appear on the horizon. These include the much-discussed no-code revolution, which abstracts away much of the noise associated with software development and opens the door to a much wider testing base.

    AI- and machine-learning-based testing is also on the horizon, yet there’s a significant challenge that must be overcome before this can happen at speed and scale. To develop mobile app tests with true intelligence and maximum efficiency, machines must be capable of autonomously completing the following steps:

    1. Comprehension: Draw from the ability to understand what’s changing in an app. For example, the machine must be able to detect differences and issues in a signup sequence or a checkout screen change.
    2. Impact analysis: The machine must know what test cases can cover that change. This sort of identification can be quite tricky.
    3. Test case generation: Next, the machine must possess the ability to generate test cases related to steps one and two. To do this, the machine must draw from several data sets. These include:
      1. Extent test collateral/test cases with product code
      2. Data from actual customer usage so that numbers one and two above may be identified
      3. What user environments look like, including information like how many users are active in the United States and in Europe
      4. Automatic execution: Perhaps the most crucial need is that the machine can perform testing entirely by itself. With the ability to self-execute tests, we’ll have reached a new era in testing.
      5. Reports: Before the testing cycle can begin again, the machine must be able to produce detailed reports that make sense to its human handlers. When it comes to test results, the more detail the machine can provide in as approachable a manner as possible, the better.

    Problems and Solutions

    Some testing platforms are now capable of many of the tasks I highlight above, and quality assurance teams that move away from self-coding tests and toward the future of testing stand to benefit from these solutions (particularly when their competitors do not).

    Partially enabled by AI and ML, no-code solutions provide a stopgap solution until machines can really get a handle on the above five steps. At this point, it’s really just a matter of time: We can already see glimpses of a wholly automated testing cycle where human input is limited and machines do the heavy lifting.

    It’s easier than ever to imagine a world where there’s no need for testing to be an afterthought and software disasters have become a thing of the past.