I tend to spend a large portion of my development time worrying about the various interfaces across the application. I like to worry about UX (aka the interface between the user and my app). I like to worry about the ORM (aka the interface between the database and my code). And I especially like to worry about the client-side service layer (aka the interface between the backend and the frontend). When I worry, I very quickly find myself writing tests.

The new hotness in Flex testing is, of course, FlexMonkey, developed and open-sourced by my company, Gorilla Logic. The next best Flex testing platform, and the new hotness in its own right, is FlexUnit 4, developed and open-sourced by our partners at Digital Primates. FlexUnit 4 is the Flex 4 unit testing framework. Because of its awesome async testing support, along with many other great features, it is ideally suited to test client-side service layers. In this post, I’m going to explore async testing with FlexUnit 4 to better understand how I can help mitigate the pain of asynchronous backend services that are ever-present in enterprise Flex applications.

Test: Create Team

Let’s imagine I have my favorite data model of teams and players, with a one-to-many relationship between the two entities. Next, let’s assume that I wrote a beautiful client-side service layer that has both basic CRUD operations like create team and delete team, and more complex operations like trade player. I’d like to cover everything with a set of tests so I can spend my time worrying about other things.

Here’s a simple async test case for the basic create team operation:

public function createTeam():void {
    var token:AsyncToken = service.createTeam('Los Angeles Lakers');
    token.addResponder(Async.asyncResponder(this, new TestResponder(createTeam2, fault), TIMEOUT));
public function createTeam2(event:ResultEvent, passThroughData:Object):void {
    var token:AsyncToken = service.getAllTeams();
    token.addResponder(Async.asyncResponder(this, new TestResponder(createTeam3, fault), TIMEOUT));
public function createTeam3(event:ResultEvent, passThroughData:Object):void {
    var teams:ArrayCollection = event.result as ArrayCollection;
    assertThat('Team not created', 'Los Angeles Lakers', inArray(teams.toArray()));

First, we create a new team, then we load all the teams, and lastly, we verify that the newly created team is in the list. There are two important things to note: async stuff is everywhere ([Test(async)] metadata, AsyncToken, AsyncResponder, etc.), and there is a chain of functions (createTeam() chains to createTeam2() which chains to createTeam3()). In particular, the chain pattern is characteristic of any async testing. Every single non-trivial async test involves a chain of function calls to do the work of testing an asynchronous backend.

Here’s a simple diagram of the chain for the create team test:


Each diagram box is just a logic operation in our test, and they also happen to correspond exactly to the functions that make up the test chain.

Test: Trade Player

When testing the more complex client-side service layer operations, or simply writing more complex tests, the chain pattern often develops branches and sub-chains as various pieces of state are verified asynchronously.

A good example is the trade player operation, which we might test using a chain with two branches: one to verify the player was removed from old team, and one to verify the player was added to the new team. Here’s the diagram:


We don’t really care what goes on inside the client-side service layer to achieve this, or even what happens on the backend (it’s probably just as simple as changing the team_id column on the players table to the new team’s id). We only care that the test passes.

And the accompanying test code:

public function tradePlayer():void {
    var token:AsyncToken = service.tradePlayer('Carmelo Anthony', 'Denver Nuggets', 'Cleveland Cavaliers');
    token.addResponder(Async.asyncResponder(this, new TestResponder(tradePlayer2, fault), TIMEOUT));
public function tradePlayer2(event:ResultEvent, passThroughData:Object):void {
    var token:AsyncToken = service.getPlayersByTeam('Denver Nuggets');
    token.addResponder(Async.asyncResponder(this, new TestResponder(tradePlayer3, fault), TIMEOUT));
    var token2:AsyncToken = service.getPlayersByTeam('Cleveland Cavaliers');
    token2.addResponder(Async.asyncResponder(this, new TestResponder(tradePlayer4, fault), TIMEOUT));
public function tradePlayer3(event:ResultEvent, passThroughData:Object):void {
    var players:ArrayCollection = event.result as ArrayCollection;
    assertThat('Traded player not removed from old team', 'Carmelo Anthony', not(inArray(players.toArray())));
public function tradePlayer4(event:ResultEvent, passThroughData:Object):void {
    var players:ArrayCollection = event.result as ArrayCollection;
    assertThat('Traded player not added to new team', 'Carmelo Anthony', inArray(players.toArray()));

The interesting part occurs in the second step in the chain, tradePlayer2(). In this function, we use a pair of AsyncTokens, to fork the chain into two sub-chains. One sub-chain gets all the players on the old team and verifies that the traded player has been removed. And the other sub-chain gets all the players on the new team and verifies that the trade player has been added.

A Better Approach

Right now, the chained function approach is the only approach for testing an asynchronous client-side service layer. As another example, you can see the chained function approach appears again when I tested an LCDS-powered backend in my Getting Real with LCDS, Part 1 article at

There has got to be something better, right? Chained functions work fine, but boy are they ugly looking in code. I’ve been having a discussion on the FlexUnit forums about better async testing. The general wisdom is that one could use the Sequence interfaces to build an async action and have the SequenceRunner manage the chain. Currently, the best documentation on Sequences is the old Fluint wiki doc. In enterprise Flex development, async backends tend to swarm like locusts, so I hope to have some code to show soon to streamline the testing process.



We’re pretty big on testing at Gorilla Logic, and in the world of Flex that usually means using FlexMonkey to test the UI and using FlexUnit to test the code. Alas, it is a huge pain in the ass to correctly test the many async objects and services inherent in any Flex app with FlexUnit. Enter Fluint, an superior Flex unit tesing framework by the cool guys at digital primates (no relation). Fluint is the heir apparent to take over the unit testing crown from the venerable FlexUnit. So let’s take Fluint and its enhanced async testing support for a spin.

Service Layer

First, assume we have a nice service layer in Flex that talks asynchronously to our backend. Just something simple to start:

public class MyService {
    public function getSomething(result:Function, fault:Function):AsyncToken {
        //call the backend
        var token:AsyncToken = backend.getSomething();
        //wire the callbacks to the result
        token.addResponder(new AsyncResponder(result, fault, token));
        return token;

In this example, our service only has one method, getSomething() that takes two callback functions. It simply calls the backend method, wires up the callbacks (which get called when the backend method returns a result), and returns the token. It is absolutely critical that our callback-powered service method return the AsyncToken. The reason for this will become apparent.

We might use our service like this:

<?xml version="1.0" encoding="utf-8"?>
        private var service:MyService;
        private function complete():void {
            service = new MyService();
            service.getSomething(resultHandler, faultHandler);
        private function resultHandler(result:Object, token:Object=null):void {
            lbl.text =;
        public function faultHandler(error:Object, token:Object=null):void {
            lbl.text = 'fault';
    <mx:Label id="lbl" text="initial" />

We make a call our service, and then use the callbacks to alter the UI however we want depending on the result. In common usage, the fact that our service returns an AsyncToken is worthless, it might as well return void. So, why did I say this is critical? Throw Fluint testing into the mix and it’s “Show em what’s behind door number 2, Johnny!”

Fluint Testing

Fluint provides two different async wrapper methods: asyncHandler and asyncResponder. The first allows a test to be wired to an async method by events, the second allows a test to be wired to an async method by a responder. Since the service method we’re trying to test doesn’t throw any events, we’ll need to use the latter. So inside a Fluint test case, we have our test method:

public function testGetSomething():void {
    //call service with dummy callback
    var token:AsyncToken = service.getSomething(dummyResult, dummyFault);
    //create async test responder
    var responder:IResponder = asyncResponder(
            new TestResponder(testHandler, faultHandler), 1000, token);
    //wire test responder as 2nd callback
private function testHandler(result:Object, passThroughData:Object):void {

The trick is to wire a second callback via Fluint’s asyncResponder helper that actually does the testing, and just give the original service call some dummy callbacks. Note that if the service method didn’t return its AsyncToken there would be no way to wire a second callback. The Fluint async helper do two import operations: they handle the event or call the callback AND they mark the test method as an async method so the result is correctly reported by the test harness. You can read more about Async Testing in Fluint’s wiki. The rest of Fluint is your standard chain of crap borrowed from JUnit: test runner, test suites, and test cases.

Digging Deeper: It is equally critical to use dummy callbacks in the original service method call because in a failure situation they will cause Flash Player to error out instead of being caught by Fluint and reported as a test failure.


The complete code is up on GitHub here: test_fluint_async. The code is MIT licensed and includes a working fluint.swc (see below) plus a mock async backend (so timeouts and faults are easily testable).

Alas, Fluint v1.1.0 was built incorrectly and is missing the TestResponder class (see issue 35). So if you want to try out Fluint in your project, I recommend you grab it from svn and build the swc yourself. Hopefully, this will all be fixed in the next release.

UPDATE: Fluint v1.1.1 was release on May 1, 2009 and fixes this issues and a few others. Download it here.

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