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On the utility of user stories

2021-10-16T00:00:00Z

User stories are a staple of most agile methodologies. You’d be hard-pressed to find an experienced software developer that’s not come across them at some point in their career. In case you haven’t, they look something like this:

As a frequent customer,
I want to be able to browse my previous orders,
So that I can quickly re-order products.

They provide a persona (in this case “a frequent customer”), a goal (“browse my previous orders”) and a reason (“so that I can quickly re-order products”). This fictitious user story would probably rank among one of the better ones I’ve seen. More typically you end up with something like:

As a user,
I want to be able to login,
So that I can browse while logged in.

This doesn’t really provide a persona or any proper reasoning. It’s just a straight-forward task pretending to be a user story. If this is written in an issue then it provides no extra information over one that simply says “Allow users to login”. In fact, because it’s expressed so awkwardly I’d argue that it’s worse.

This kind of task-disguised-as-a-user-story problem becomes more obvious when people try to write technical tasks in the same way:

As a developer,
I want to refactor the JobFactory,
So that I can work with it more efficiently in the future.

This just says “Refactor the JobFactory”. If you wrote that in a ticket you’d probably feel bad for not describing it very well, but somehow when it’s dressed up as a user story it feels more valuable.

Does the user really want that?

One thing that really irks me about user stories is that it lets you twist your business objectives into sounding like they’re the user’s idea: the story becomes a post-hoc justification for a task you decided was required.

Say you’re making a mobile app for an online book store, and your team for whatever reason has a target of increasing the number of users who view the daily book-of-the-day offer. Maybe you do some interviews and users tell you they forget to check in each day to see what the offer is. How can you funnel more users there?

As a mobile app user,
I want to receive a push notification whenever a new book-of-the-day is available,
So that I have the chance to buy the book.

Some users probably do want such a thing, but I’d argue the vast majority of them do not. Imagine if every app on your phone alerted you whenever there was a new deal, or popped up a dialog whenever you went near a physical shop they had vouchers for…

Obviously in the cold reality of capitalism businesses make money by doing things not strictly in the interests of users¹. When written up like this it becomes so painfully disingenuous, though. Despite writing a user story that starts with the words “As a user”, you’re not really putting yourself in the user’s shoes.

Who even is the user?

One of the big benefits of user stories comes from using personas to describe users. It’s also one of the things that’s rarely actually done, at least in my experience. Looking at Google Trends you can see the rise of searches for “user story” as agile slowly takes over the world, but the movement in searches about personas is very slight:

Graph showing relative search frequency for user stories against user personas

A lot of the time stories are just written with “As a user”, or have some adjectives tacked on to the start (“as a mobile user”, “as a logged-in user”). The best I’ve ever seen in the wild was specifying the class of user like in the example at the start: “as a frequent customer”, or “as a visually impaired user”.

The problem with using these classes is it requires you to come up with them when you’re writing the story. Maybe one day you think about visually impaired users, but the next you don’t. Maybe Bob thinks about certain classes of users, but Alice concentrates on different ones.

The ideal way to solve this is to come up with personas that all the team understand. For example:

Kiera is addicted to books. She reads across genres, and often buys books to gift to her friends and family. She has piles and piles of books to read, but that doesn’t stop her ordering more if she sees a good deal. She likes receiving new books almost as much as reading them, and opts for the fastest delivery available.
Sharon is a slow, methodical reader. She buys one book at a time when she’s close to finishing her current one, and gifts or resells her old books. She almost exclusively reads Science Fiction, and will generally read complete series from start to finish. She’s short-sighted and often struggles when using mobile phones or computers.

You’d probably want 2-4 personas that collectively represent most facets of your userbase. They can be a lot more fleshed out than these - if you search for example user personas you’ll find many beautifully presented examples that have complete backgrounds including hobbies, education levels, and so on. Even with this minimal level of detail, though, I’d argue they’re more useful than just writing things in a standard user story form.

Thinking back to the story about push notifications, writing it to use one of these two personas forces you to think about the trade-offs involved. Kiera probably would like a notification, but it would annoy and possibly confuse Sharon. This then leads you down the path of considering how to accommodate both types of user — maybe adding it as an option, or doing some fancy machine learning, etc. The conversation is now focused around the users, rather than steamrolling over them to reach a business objective.

You’re holding it wrong

The problems I’ve described are not a problem with user stories per se, but rather common issues with how they’re used. But there’s only so many times you can tell people they’re holding a tool wrong before you have to accept that maybe the tool was badly designed.

Considering features from the perspective of multiple personas is the single best thing you can possibly do to ensure you’re providing value to your users. You don’t even need to write things in the typical user story style to benefit from this.

Tacking “As a user,” to the start of all your JIRA tickets isn’t being agile, and isn’t good for users, even if it lets you tick a box somewhere. In some cases this lip-service to users is actively detrimental to them. We should be valuing users and personas over stilted templates and check-box exercises (remind you of anything?).

As a user, I want to pay more money for the things that I buy, so that the company’s CEO can afford to go to space. ↩︎

Android testing with Espresso and Spoon

2017-05-16T00:00:00Z

I’ve been spending some time recently setting up automated testing for our collection of Android apps and libraries at work. We have a mixture of unit tests, integration tests, and UI tests for most projects, and getting them all to run reliably and automatically has posed some interesting challenges.

Running tests on multiple devices using Spoon

Spoon is a tool developed by Square that handles distributing instrumentation tests to multiple connected devices, aggregating the results, and making reports.

As part of our continuous integration we build both application and test APKs, and these are pushed to the build server as build artefacts. A separate build job then pulls these artefacts down to a Mac Mini we have in the office, and executes Spoon with a few arguments:

java -jar spoon-runner.jar \
    --apk application.apk \
    --test-apk applicationTests.apk \
    --fail-on-failure \
    --fail-if-no-device-connected

Spoon finds all devices, deploys both APKs on them, and then begins the instrumentation tests. We use two physical devices and an emulator to cover the form factors and API versions that are important to us; if any test fails on any of those devices, Spoon will return an error code and the build will fail.

For library projects, you only have a single APK containing both the tests and the library itself. The current version of Spoon requires both --apk and --test-apk to be specified, so we simply pass in the same APK to both. It looks like future versions of Spoon will be more flexible in this regard.

Spoon produces HTML reports, showing the status of each test run on each device. We have the report output folder collected as a build artefact, so the reports can be seen right from the build server:

Spoon output summary, showing results of 171 tests run on 3 devices

Flake-free UI testing with Espresso

Espresso is an Android library that provides an API for interacting with and making assertions about the UI of Android applications. Espresso has a very simple interface, and does lots of clever things under the hood to ensure that your tests only execute code when the UI is idle (and hence stable). You shouldn’t ever need to make your code sleep or wait.

In order for Espresso’s magic to work, it needs to know whenever some background activity is going on that it needs to wait for. By default, it hooks in to Android’s AsyncTask executor so it can wait for those to finish. In our apps, there were a few cases where we used an explicit Thread to do some background work, which caused tests to fail intermittently (depending on whether the thread performed its UI update before or after Espresso executed the test code). Rewriting these cases to use an AsyncTask enabled Espresso to figure out what was happening and the tests started passing reliably.

Another, similar, problem occurred where we were using RxJava to load some data. There are two possible ways to deal with this… Espresso has a concept of an idling resource, which provides a way of telling Espresso when a resource is busy so it can belay interacting with or testing the UI until the resource is finished. In our case, the code in question was going to be rewritten soon, so we went for a quicker and dirtier option: force RxJava to use the same executor as AsyncTask.

To do this, we added a simple test utility class that registers an RxJavaPlugin that overrides the Schedulers used by Rx:

/**
 * Hooks in to the RxJava plugins API to force Rx work to be scheduled on the
 * AsyncTask's thread pool executor. This is a quick and dirty hack to make
 * Espresso aware of when Rx is doing work (and wait for it).
 */
public final class RxSchedulerHook {

    private static final RxJavaSchedulersHook javaHook =
            new RxJavaTestSchedulerHook();

    private RxSchedulerHook() {
        // Should not be insantiated
    }

    public static void registerHooksForTesting() {
        if (RxJavaPlugins.getInstance().getSchedulersHook() != javaHook) {
            RxJavaPlugins.getInstance().reset();
            RxJavaPlugins.getInstance().registerSchedulersHook(javaHook);
        }
    }

    private static class RxJavaTestSchedulerHook extends RxJavaSchedulersHook {
        @Override
        public Scheduler getComputationScheduler() {
            return Schedulers.from(AsyncTask.THREAD_POOL_EXECUTOR);
        }

        @Override
        public Scheduler getIOScheduler() {
            return Schedulers.from(AsyncTask.THREAD_POOL_EXECUTOR);
        }

        @Override
        public Scheduler getNewThreadScheduler() {
            return Schedulers.from(AsyncTask.THREAD_POOL_EXECUTOR);
        }
    }
}

With the hook registered Rx does all of its work on the same thread pool as AsyncTask, which Espresso already knows about. It’s not the best long-term solution, but it means we don’t have to spend time integrating IdlingResource for code that doesn’t have long to live. With the hook in place, the tests that were flaking because of Rx started passing reliably as well.

Getting automatic screenshots of failures

Spoon provides a client library to, among other things, take a screenshot of the device. Espresso provides a hook that can be used to change how errors are handled. Putting the two together is very simple:

final FailureHandler defaultHandler =
        new DefaultFailureHandler(
                InstrumentationRegistry.getTargetContext());

Espresso.setFailureHandler(new FailureHandler() {
    @Override
    public void handle(Throwable throwable, Matcher<View> matcher) {
        try {
            Spoon.screenshot(
                    getActivity(),
                    "espresso-failure",
                    description.getClassName(),
                    description.getMethodName());
        } catch (Exception ex) {
            Log.e(TAG, "Error capturing screenshot", ex);
        }
        defaultHandler.handle(throwable, matcher);
    }
});

In our new error handler we simply ask Spoon to take a screenshot, then call Espresso’s original handler so that it can output its debugging information and fail the test. The Spoon runner automatically picks up the screenshot and adds it to the report:

Spoon output details, showing a screenshot captured of the failure

Having the screenshot, error message and logs all presented in a clean UI makes debugging failures much, much easier than searching through a huge build log to try and find the exception.

Filtering tests based on device capabilities

Some tests won’t work on every device you throw at them. We had two problems: some tests require a higher API version than some of our devices, and some of the UIs under test were designed to run only on certain resolutions.

The main cause for our dependence on newer API versions was the use of WireMock, a brilliant library for stubbing out web services. WireMock requires API 19, while our physical devices tend to run versions older than that. Stopping these tests running is simply a case of applying an annotation to the class:

@SdkSuppress(minSdkVersion=19)

Screen resolution is a bit more complicated. One of our apps is designed for a specific tablet device (and will never be used on anything else), and trying to render the UI on smaller screens results in items overlapping, important parts ending up below the fold, and other problems.

We’d still like all the other tests for that app to run on all of the devices, though, so we can test them on a variety of API versions and in other conditions. We just need to suppress the UI tests. To do this, we subclassed the Android ActivityTestRule and overrode the apply method:

@Override
public Statement apply(Statement base, final Description description) {
    if (!canRunUiTests(InstrumentationRegistry.getContext())) {
        // If we can't run UI tests, then return a statement that does nothing
        // at all.  With normal JUnit tests we'd just throw an assumption
        // failure and the test would be ignored, but that makes the Android
        // runner angry.
        return new Statement() {
            @Override
            public void evaluate() throws Throwable {
                // Do nothing
            }
        };
    }

    return super.apply(base, description);
}

/**
 * Checks that the screen size is close enough to that of our tablet device.
 */
@TargetApi(Build.VERSION_CODES.HONEYCOMB_MR2)
private boolean canRunUiTests(Context context) {
    if (Build.VERSION.SDK_INT < Build.VERSION_CODES.HONEYCOMB_MR2) {
        return false;
    }
    int screenWidth = dpToPx(context,
            context.getResources().getConfiguration().screenWidthDp);
    return screenWidth >= 600;
}

private int dpToPx(Context context, int dp) {
    DisplayMetrics displayMetrics = context.getResources().getDisplayMetrics();
    return Math.round(dp * displayMetrics.density);
}

When the rule is run, we check if the screen width meets a minimum number of pixels. If it doesn’t, an empty Statement is returned that turns the test into a no-op. These show up as passed rather than skipped in the output, but there doesn’t seem to be a nice way to signal to the Android JUnit runner that the test is being ignored programatically.