近年来，在为几个项目编写线程处理代码时，我多次遇到过这个问题。我提供了一个迟来的答案，因为大多数其他答案虽然提供了替代方案，但实际上并没有回答关于测试的问题。我的答案是针对多线程代码没有替代方案的情况;为了完整性，我将讨论代码设计问题，但也将讨论单元测试。

编写可测试的多线程代码

首先要做的是将生产线程处理代码与所有执行实际数据处理的代码分开。这样，数据处理就可以作为单线程代码进行测试，多线程代码所做的唯一事情就是协调线程。

The second thing to remember is that bugs in multithreaded code are probabilistic; the bugs that manifest themselves least frequently are the bugs that will sneak through into production, will be difficult to reproduce even in production, and will thus cause the biggest problems. For this reason, the standard coding approach of writing the code quickly and then debugging it until it works is a bad idea for multithreaded code; it will result in code where the easy bugs are fixed and the dangerous bugs are still there.

相反，在编写多线程代码时，必须抱着一种从一开始就避免编写错误的态度来编写代码。如果您已经正确地删除了数据处理代码，线程处理代码应该足够小——最好只有几行，最坏也就几十行——这样您就有机会在不编写错误的情况下编写它，当然也不会编写很多错误，如果您了解线程，请慢慢来，并且小心。

为多线程代码编写单元测试

一旦尽可能仔细地编写了多线程代码，仍然值得为该代码编写测试。测试的主要目的与其说是测试高度依赖于时间的竞争条件错误(不可能重复测试这种竞争条件)，不如说是测试防止这种错误的锁定策略是否允许多个线程按预期进行交互。

To properly test correct locking behavior, a test must start multiple threads. To make the test repeatable, we want the interactions between the threads to happen in a predictable order. We don't want to externally synchronize the threads in the test, because that will mask bugs that could happen in production where the threads are not externally synchronized. That leaves the use of timing delays for thread synchronization, which is the technique that I have used successfully whenever I've had to write tests of multithreaded code.

If the delays are too short, then the test becomes fragile, because minor timing differences - say between different machines on which the tests may be run - may cause the timing to be off and the test to fail. What I've typically done is start with delays that cause test failures, increase the delays so that the test passes reliably on my development machine, and then double the delays beyond that so the test has a good chance of passing on other machines. This does mean that the test will take a macroscopic amount of time, though in my experience, careful test design can limit that time to no more than a dozen seconds. Since you shouldn't have very many places requiring thread coordination code in your application, that should be acceptable for your test suite.

Finally, keep track of the number of bugs caught by your test. If your test has 80% code coverage, it can be expected to catch about 80% of your bugs. If your test is well designed but finds no bugs, there's a reasonable chance that you don't have additional bugs that will only show up in production. If the test catches one or two bugs, you might still get lucky. Beyond that, and you may want to consider a careful review of or even a complete rewrite of your thread handling code, since it is likely that code still contains hidden bugs that will be very difficult to find until the code is in production, and very difficult to fix then.

并发是内存模型、硬件、缓存和代码之间复杂的相互作用。在Java的情况下，至少这样的测试主要由jcstress部分解决。众所周知，该库的创建者是许多JVM、GC和Java并发特性的作者。

但是即使是这个库也需要对Java内存模型规范有很好的了解，这样我们才能确切地知道我们在测试什么。但我认为这项工作的重点是微基准测试。不是庞大的业务应用。

等待在帮助您编写确定性单元测试时也很有用。它允许您等待系统中的某个状态更新。例如:

await().untilCall( to(myService).myMethod(), greaterThan(3) );

or

await().atMost(5,SECONDS).until(fieldIn(myObject).ofType(int.class), equalTo(1));

它还支持Scala和Groovy。

await until { something() > 4 } // Scala example

看看我的相关答案在

为自定义Barrier设计一个Test类

它偏向于Java，但对选项进行了合理的总结。

总而言之(我认为)，它不是使用一些花哨的框架来确保正确性，而是如何设计你的多线程代码。拆分关注点(并发性和功能性)有助于提高信心。测试引导的面向对象软件的发展比我能更好地解释一些选项。

静态分析和形式化方法(参见并发性:状态模型和Java程序)是一种选择，但我发现它们在商业开发中用处有限。

不要忘记，任何加载/浸泡风格的测试都很少能保证突出问题。

好运！

我在测试多线程代码时也遇到了严重的问题。然后我在Gerard Meszaros的“xUnit测试模式”中找到了一个非常酷的解决方案。他描述的模式被称为Humble object。

基本上，它描述了如何将逻辑提取到独立的、易于测试的组件中，该组件与环境解耦。在你测试了这个逻辑之后，你可以测试复杂的行为(多线程，异步执行，等等…)

(如果可能的话)不要使用线程，使用actor /活动对象。易于测试。