We are developing a WPF application using TDD. As we're already working on this solution for almost two years, we've written a huge bunch of tests (almost 2000 Unittests right now).
There are some classes, that need to implement functionality multithreaded and asynchronously. For example a communication-component that can both send and receive messages and parse them. The dependencies are always mocked using RhinoMocks.
Our Test-Methods targeting these classes look very similar, as following:
[TestMethod]
public void Method_Description_ExpectedResult(){
// Arrange
var myStub = MockRepository.GenerateStub<IMyStub>();
var target = new MyAsynchronousClass(myStub);
// Act
var target.Send("Foo");
Thread.Sleep(200);
//Assert
myStub.AssertWasCalled(x => x.Bar("Foo"));
}
As you can see, this test runs at least for 200 ms due to the Thread.Sleep(). We optimized the test replacing the AssertWasCalled with a active polling method, s.th. like this:
public static bool True(Func<bool> condition, int times, int waitTime)
{
for (var i = 0; i < times; i++)
{
if (condition())
return true;
Thread.Sleep(waitTime);
}
return condition();
}
We can now use this WaitFor.True(...) Method by changing the AssertWasCalled to:
var fooTriggered = false;
myStub.Stub(x => x.Bar("Foo")).Do((Action)(() => fooTriggered = true)));
WaitFor.True(() => fooTriggered, 20, 20);
Assert.IsTrue(fooTriggered);
This construct will terminate earlier if the condition matches, but anyway - this takes too long for us. Running all of our 2000 Tests need about 5 Minutes (building and running them).
Is there any smart trick how we could optimize code like this?
You can use a monitor. I'm making this up so please excuse me if it isn't quite compiling, but it'll look something like:
[TestMethod]
public void Method_Description_ExpectedResult(){
// Arrange
var waitingRoom = new object();
var myStub = MockRepository.GenerateStub<IMyStub>();
myStub.Setup(x => x.Bar("Foo")).Callback(x =>
{
Monitor.Enter(waitingRoom);
Monitor.Pulse(waitingRoom);
Monitor.Exit(waitingRoom);
}
var target = new MyAsynchronousClass(myStub);
// Act
Monitor.Enter(waitingRoom);
target.Send("Foo");
Monitor.Wait(waitingRoom);
Monitor.Exit(waitingRoom);
//Assert
myStub.AssertWasCalled(x => x.Bar("Foo"));
}
Code written within the Monitor can't run until it's free. The test will cause the acting thread to wait until Monitor.Wait has been called. Then the callback can enter and pulse the Monitor. The test then "wakes up", and once the callback has exited the monitor, it gets control back and exits too, allowing you to Assert.
The only thing I haven't covered is that if Bar("Foo") doesn't get called it will hang, so you might want to have a timer pulse the thread too.
You can create a class which does the complex monitoring bits for you if you use it a lot. This is one I wrote to deal with asynchronous checks in UI automation; adapting it for what you're doing might help you.
Related
How can I run a single method multiple times multi-threaded when called as a method of a class?
At first I tried to use the cluster module, but I realize it just re-runs the whole process from the start, rightfully so.
How can I achieve something like what's outlined below?
I want a class's method to spawn n processes, and when the parallel tasks are completed, I can resolve a promise which the method returns.
The problem with the code below is that calling cluster.fork() will fork index.js process.
index.js
const Person = require('./Person.js');
var Mary = new Person('Mary');
Mary.run(5).then(() => {...});
console.log('I should only run once, but I am called 5 times too many');
Person.js
const cluster = require('cluster');
class Person{
run(distance){
var completed = 0;
return new Promise((resolve, reject) => {
for(var i = 0; i < distance; i++) {
// run a separate process for each
cluster.fork().send(i).on('message', message => {
if (message === 'completed') { ++completed; }
if (completed === distance) { resolve(); }
});
}
});
}
}
I think the short answer is impossible. It's even worse - this has nothing to do with js. To multi (process or thread) in your particular problem you will essentially need a copy of the object in every thread, since it needs (maybe) access to fields - in this case you would need to either initialize it in every thread or share memory. That last one I don't think is provided in cluster, and not trivial in other languages in every use case.
If the calculation is independent of the Person I suggest you extract it, and use the usual (in index.js):
if(cluster.isWorker) {
//Use the i for calculation
} else {
//Create Person, then fork children in for loop
}
You then collect the results and change the Person as needed. You will be copying index.js, but this is standard and you only run what you need.
The problem is if results are dependent on Person. If these are constant for all i you can still send them to your forks independently. Otherwise what you have is the only way to fork. In general forking in cluster is not meant for methods, but for the app itself, which is the standard forking behavior.
Another solution
Following your comment, I suggest you checkout child_process.execFile or child_process.exec on same file.
This way you can spawn a totally independent process on the fly. Now instead of calling cluster.fork you call execFile. You can use either the exit code or stdout as return values (stderr etc.). Promise is now replaced with:
var results = []
for(var i = 0; i < distance; i++) {
// run a separate process for each
results.push(child_process.execFile().child.execFile('node', 'mymethod.js`,i]));
}
//... catch the exit event from all results or return a callback using results.
Inside mymethod.js Have your code that takes i and returns what you want either in the exit code or through stdout, both properties of the returned child_process. This is a bit un-node.js-y since you're waiting on asynchronous calls, but you're requirements are non standard. Since I'm not sure how you use this perhaps returning a callback with the array is a better idea.
How can I correctly perform something like sleep function using getTimer()? I need to do an action every 15 seconds. The code below doesn't work. I compile it with mtasc compiler on Linux.
class Tuto
{
static var lastMsg = 0;
static var msgInt = 15000;
static function main(mc)
{
if(getTimer() > lastMsg + msgInt)
{
trace("something");
lastMsg = getTimer();
}
}
}
The main instruction will be executed just once. You have to build some kind of loop or rely on the tick events sent by the player to execute your code continuously.
The basic options are:
while (true) { doSomething() }
this will execute forever, but remember that the flashplayer is single threaded so while that runs everything else will be frozen, UI and user inputs included. this is only "good" if you are building some heavy-processing tool that has no need of interacting with the user.
setInterval(doSomething, 15000)
this creates an interval that will call your function every X milliseconds. This is the simplest option and probably what you're looking for.
addEventListener(Event.ENTER_FRAME, doSomething)
this registers a listener for the ENTER_FRAME event of the Flash Player, which will be dispatched 30 times per second (by default). Inside that function you can check the current time with getTimer() and decide if it's time to execute your logic.
When I analyse code coverage in Visual Studio 2012, any of the await lines in async methods are showing as not covered even though they are obviously executing since my tests are passing. The code coverage report says that the uncovered method is MoveNext, which is not present in my code (perhaps it's compiler-generated).
Is there a way to fix code coverage reporting for async methods?
Note:
I just ran coverage using NCover, and the coverage numbers make a lot more sense using that tool. As a workaround for now, I'll be switching to that.
This can happen most commonly if the operation you're awaiting is completed before it's awaited.
I recommend you test at least synchronous and asynchronous success situations, but it's also a good idea to test synchronous and asynchronous errors and cancellations.
The reason the code is not shown as being covered has to do with how async methods are implemented. The C# compiler actually translates the code in async methods into a class that implements a state machine, and transforms the original method into a stub that initialized and invokes that state machine. Since this code is generated in your assembly, it is included in the code coverage analysis.
If you use a task that is not complete at the time the code being covered is executing, the compiler-generated state machine hooks up a completion callback to resume when the task completes. This more completely exercises the state machine code, and results in complete code coverage (at least for statement-level code coverage tools).
A common way to get a task that is not complete at the moment, but will complete at some point is to use Task.Delay in your unit test. However, that is generally a poor option because the time delay is either too small (and results in unpredictable code coverage because sometimes the task is complete before the code being tests runs) or too large (unnecessarily slowing the tests down).
A better option is to use "await Task.Yield()". This will return immediately but invoke the continuation as soon as it is set.
Another option - though somewhat absurd - is to implement your own awaitable pattern that has the semantics of reporting incomplete until a continuation callback is hooked up, and then to immediately complete. This basically forces the state machine into the async path, providing the complete coverage.
To be sure, this is not a perfect solution. The most unfortunate aspect is that it requires modification to production code to address a limitation of a tool. I would much prefer that the code coverage tool ignore the portions of the async state machine that are generated by the compiler. But until that happens, there aren’t many options if you really want to try to get complete code coverage.
A more complete explanation of this hack can be found here: http://blogs.msdn.com/b/dwayneneed/archive/2014/11/17/code-coverage-with-async-await.aspx
There are situations where I don't care about testing the async nature of a method but just want to get rid of the partial code coverage. I use below extension method to avoid this and it works just fine for me.
Warning "Thread.Sleep" used here!
public static IReturnsResult<TClass> ReturnsAsyncDelayed<TClass, TResponse>(this ISetup<TClass, Task<TResponse>> setup, TResponse value) where TClass : class
{
var completionSource = new TaskCompletionSource<TResponse>();
Task.Run(() => { Thread.Sleep(200); completionSource.SetResult(value); });
return setup.Returns(completionSource.Task);
}
and the usage is similar to the Moq's ReturnsAsync Setup.
_sampleMock.Setup(s => s.SampleMethodAsync()).ReturnsAsyncDelayed(response);
I created a test runner that runs a block of code multiple times and varies the task that is delayed using a factory. This is great for testing the different paths through simple blocks of code. For more complex paths you may want to create a test per path.
[TestMethod]
public async Task ShouldTestAsync()
{
await AsyncTestRunner.RunTest(async taskFactory =>
{
this.apiRestClient.GetAsync<List<Item1>>(NullString).ReturnsForAnyArgs(taskFactory.Result(new List<Item1>()));
this.apiRestClient.GetAsync<List<Item2>>(NullString).ReturnsForAnyArgs(taskFactory.Result(new List<Item2>()));
var items = await this.apiController.GetAsync();
this.apiRestClient.Received().GetAsync<List<Item1>>(Url1).IgnoreAwait();
this.apiRestClient.Received().GetAsync<List<Item2>>(Url2).IgnoreAwait();
Assert.AreEqual(0, items.Count(), "Zero items should be returned.");
});
}
public static class AsyncTestRunner
{
public static async Task RunTest(Func<ITestTaskFactory, Task> test)
{
var testTaskFactory = new TestTaskFactory();
while (testTaskFactory.NextTestRun())
{
await test(testTaskFactory);
}
}
}
public class TestTaskFactory : ITestTaskFactory
{
public TestTaskFactory()
{
this.firstRun = true;
this.totalTasks = 0;
this.currentTestRun = -1; // Start at -1 so it will go to 0 for first run.
this.currentTaskNumber = 0;
}
public bool NextTestRun()
{
// Use final task number as total tasks.
this.totalTasks = this.currentTaskNumber;
// Always return has next as turn for for first run, and when we have not yet delayed all tasks.
// We need one more test run that tasks for if they all run sync.
var hasNext = this.firstRun || this.currentTestRun <= this.totalTasks;
// Go to next run so we know what task should be delayed,
// and then reset the current task number so we start over.
this.currentTestRun++;
this.currentTaskNumber = 0;
this.firstRun = false;
return hasNext;
}
public async Task<T> Result<T>(T value, int delayInMilliseconds = DefaultDelay)
{
if (this.TaskShouldBeDelayed())
{
await Task.Delay(delayInMilliseconds);
}
return value;
}
private bool TaskShouldBeDelayed()
{
var result = this.currentTaskNumber == this.currentTestRun - 1;
this.currentTaskNumber++;
return result;
}
public async Task VoidResult(int delayInMilliseconds = DefaultDelay)
{
// If the task number we are on matches the test run,
// make it delayed so we can cycle through them.
// Otherwise this task will be complete when it is reached.
if (this.TaskShouldBeDelayed())
{
await Task.Delay(delayInMilliseconds);
}
}
public async Task<T> FromResult<T>(T value, int delayInMilliseconds = DefaultDelay)
{
if (this.TaskShouldBeDelayed())
{
await Task.Delay(delayInMilliseconds);
}
return value;
}
}
I'm currently trying to reduce the number of similar requests being processed in a business layer by:
Caching the requests a method receives
Performing the slow processing task (once for all similar requests)
Return the result to each requesting method calls
Things to note, are that:
The original method calls are not currently in a async BeginMethod() / EndMethod(IAsyncResult)
The requests arrive faster than the time it takes to generate the output
I'm trying to use TPL where possible, as I am currently trying to learn more about this library
eg. Improving the following
byte[] RequestSlowOperation(string operationParameter)
{
Perform slow task here...
}
Any thoughts?
Follow up:
class SomeClass
{
private int _threadCount;
public SomeClass(int threadCount)
{
_threadCount = threadCount;
int parameter = 0;
var taskFactory = Task<int>.Factory;
for (int i = 0; i < threadCount; i++)
{
int i1 = i;
taskFactory
.StartNew(() => RequestSlowOperation(parameter))
.ContinueWith(result => Console.WriteLine("Result {0} : {1}", result.Result, i1));
}
}
private int RequestSlowOperation(int parameter)
{
Lazy<int> result2;
var result = _cacheMap.GetOrAdd(parameter, new Lazy<int>(() => RequestSlowOperation2(parameter))).Value;
//_cacheMap.TryRemove(parameter, out result2); <<<<< Thought I could remove immediately, but this causes blobby behaviour
return result;
}
static ConcurrentDictionary<int, Lazy<int>> _cacheMap = new ConcurrentDictionary<int, Lazy<int>>();
private int RequestSlowOperation2(int parameter)
{
Console.WriteLine("Evaluating");
Thread.Sleep(100);
return parameter;
}
}
Here is a fast, safe and maintainable way to do this:
static var cacheMap = new ConcurrentDictionary<string, Lazy<byte[]>>();
byte[] RequestSlowOperation(string operationParameter)
{
return cacheMap.GetOrAdd(operationParameter, () => new Lazy<byte[]>(() => RequestSlowOperation2(operationParameter))).Value;
}
byte[] RequestSlowOperation2(string operationParameter)
{
Perform slow task here...
}
This will execute RequestSlowOperation2 at most once per key. Please be aware that the memory held by the dictionary will never be released.
The user delegate passed to the ConcurrentDictionary is not executed under lock, meaning that it could execute multiple times! My solution allows multiple lazies to be created but only one of them will ever be published and materialized.
Regarding locking: this solution will take locks, but it does not matter because the work items are far more expensive than the (few) lock operations.
Honestly, the use of TPL as a technology here is not really important, this is just a straight up concurrency problem. You're trying to protect access to a shared resource (the cached data) and, to do that, the only approach is to lock. Either that or, if the cache entry does not already exist, you could allow all incoming threads to generate it and then subsequent requesters benefit from the cached value once it's stored, but there's little value in that if the resource is slow/expensive to generate and cache.
Perhaps some more details will make it clear on exactly why you're trying to accomplish this without a lock. I'll happily to revise my answer if more detail makes it clearer what you're trying to do.
I am trying to use the parallel task library to kick off a number of tasks like this:
var workTasks = _schedules.Where(x => x.Task.Enabled);
_tasks = new Task[workTasks.Count()];
_cancellationTokenSource = new CancellationTokenSource();
_cancellationTokenSource.Token.ThrowIfCancellationRequested();
int i = 0;
foreach (var schedule in _schedules.Where(x => x.Task.Enabled))
{
_log.InfoFormat("Reading task information for task {0}", schedule.Task.Name);
if(!schedule.Task.Enabled)
{
_log.InfoFormat("task {0} disabled.", schedule.Task.Name);
i++;
continue;
}
schedule.Task.ServiceStarted = true;
_tasks[i] = Task.Factory.StartNew(() =>
schedule.Task.Run()
, _cancellationTokenSource.Token);
i++;
_log.InfoFormat("task {0} has been added to the worker threads and has been started.", schedule.Task.Name);
}
I want these tasks to sleep and then wake up every 5 minutes and do their stuff, at the moment I am using Thread.Sleep in the Schedule object whose Run method is the Action that is passed into StartNew as an argument like this:
_tasks[i] = Task.Factory.StartNew(() =>
schedule.Task.Run()
, _cancellationTokenSource.Token);
I read somewhere that Thread.Sleep is a bad solution for this. Can anyone recommend a better approach?
By my understanding, Thread.Sleep is bad generally, because it force-shifts everything out of memory even when that's not necessary. It won't be a big deal in most cases, but it could be a performance issue.
I'm in the habit of using this snippet instead:
new System.Threading.EventWaitHandle(false, EventResetMode.ManualReset).WaitOne(1000);
Fits on one line, and isn't overly complicated -- it creates an event handle that will never be set, and then waits for the full timeout period before continuing.
Anyway, if you're just trying to have something repeat every 5 minutes, a better approach would probably be to use a Timer. You could even make a class to neatly wrap everything if your repeated work methods are already factored out:
using System.Threading;
using System.Threading.Tasks;
public class WorkRepeater
{
Timer m_Timer;
WorkRepeater(Action workToRepeat, TimeSpan interval)
{
m_Timer = new System.Timers.Timer((double)Interval.Milliseconds);
m_Timer.Elapsed +=
new System.Timers.ElapsedEventHandler((o, ea) => WorkToRepeat());
}
public void Start()
{
m_Timer.Start();
}
public void Stop()
{
m_Timer.Stop();
}
}
Bad solution are Tasks here. Task should be used for short living operations, like asynch IO. If you want to control life time of task you should use Thread and sleep as much as you like, because Thread is individual, but Tasks are rotated in thread pool which is shared.