它并不完美，但我用c#写了这个帮助程序:

using System;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;

namespace Proto.Promises.Tests.Threading
{
    public class ThreadHelper
    {
        public static readonly int multiThreadCount = Environment.ProcessorCount * 100;
        private static readonly int[] offsets = new int[] { 0, 10, 100, 1000 };

        private readonly Stack<Task> _executingTasks = new Stack<Task>(multiThreadCount);
        private readonly Barrier _barrier = new Barrier(1);
        private int _currentParticipants = 0;
        private readonly TimeSpan _timeout;

        public ThreadHelper() : this(TimeSpan.FromSeconds(10)) { } // 10 second timeout should be enough for most cases.

        public ThreadHelper(TimeSpan timeout)
        {
            _timeout = timeout;
        }

        /// <summary>
        /// Execute the action multiple times in parallel threads.
        /// </summary>
        public void ExecuteMultiActionParallel(Action action)
        {
            for (int i = 0; i < multiThreadCount; ++i)
            {
                AddParallelAction(action);
            }
            ExecutePendingParallelActions();
        }

        /// <summary>
        /// Execute the action once in a separate thread.
        /// </summary>
        public void ExecuteSingleAction(Action action)
        {
            AddParallelAction(action);
            ExecutePendingParallelActions();
        }

        /// <summary>
        /// Add an action to be run in parallel.
        /// </summary>
        public void AddParallelAction(Action action)
        {
            var taskSource = new TaskCompletionSource<bool>();
            lock (_executingTasks)
            {
                ++_currentParticipants;
                _barrier.AddParticipant();
                _executingTasks.Push(taskSource.Task);
            }
            new Thread(() =>
            {
                try
                {
                    _barrier.SignalAndWait(); // Try to make actions run in lock-step to increase likelihood of breaking race conditions.
                    action.Invoke();
                    taskSource.SetResult(true);
                }
                catch (Exception e)
                {
                    taskSource.SetException(e);
                }
            }).Start();
        }

        /// <summary>
        /// Runs the pending actions in parallel, attempting to run them in lock-step.
        /// </summary>
        public void ExecutePendingParallelActions()
        {
            Task[] tasks;
            lock (_executingTasks)
            {
                _barrier.SignalAndWait();
                _barrier.RemoveParticipants(_currentParticipants);
                _currentParticipants = 0;
                tasks = _executingTasks.ToArray();
                _executingTasks.Clear();
            }
            try
            {
                if (!Task.WaitAll(tasks, _timeout))
                {
                    throw new TimeoutException($"Action(s) timed out after {_timeout}, there may be a deadlock.");
                }
            }
            catch (AggregateException e)
            {
                // Only throw one exception instead of aggregate to try to avoid overloading the test error output.
                throw e.Flatten().InnerException;
            }
        }

        /// <summary>
        /// Run each action in parallel multiple times with differing offsets for each run.
        /// <para/>The number of runs is 4^actions.Length, so be careful if you don't want the test to run too long.
        /// </summary>
        /// <param name="expandToProcessorCount">If true, copies each action on additional threads up to the processor count. This can help test more without increasing the time it takes to complete.
        /// <para/>Example: 2 actions with 6 processors, runs each action 3 times in parallel.</param>
        /// <param name="setup">The action to run before each parallel run.</param>
        /// <param name="teardown">The action to run after each parallel run.</param>
        /// <param name="actions">The actions to run in parallel.</param>
        public void ExecuteParallelActionsWithOffsets(bool expandToProcessorCount, Action setup, Action teardown, params Action[] actions)
        {
            setup += () => { };
            teardown += () => { };
            int actionCount = actions.Length;
            int expandCount = expandToProcessorCount ? Math.Max(Environment.ProcessorCount / actionCount, 1) : 1;
            foreach (var combo in GenerateCombinations(offsets, actionCount))
            {
                setup.Invoke();
                for (int k = 0; k < expandCount; ++k)
                {
                    for (int i = 0; i < actionCount; ++i)
                    {
                        int offset = combo[i];
                        Action action = actions[i];
                        AddParallelAction(() =>
                        {
                            for (int j = offset; j > 0; --j) { } // Just spin in a loop for the offset.
                            action.Invoke();
                        });
                    }
                }
                ExecutePendingParallelActions();
                teardown.Invoke();
            }
        }

        // Input: [1, 2, 3], 3
        // Ouput: [
        //          [1, 1, 1],
        //          [2, 1, 1],
        //          [3, 1, 1],
        //          [1, 2, 1],
        //          [2, 2, 1],
        //          [3, 2, 1],
        //          [1, 3, 1],
        //          [2, 3, 1],
        //          [3, 3, 1],
        //          [1, 1, 2],
        //          [2, 1, 2],
        //          [3, 1, 2],
        //          [1, 2, 2],
        //          [2, 2, 2],
        //          [3, 2, 2],
        //          [1, 3, 2],
        //          [2, 3, 2],
        //          [3, 3, 2],
        //          [1, 1, 3],
        //          [2, 1, 3],
        //          [3, 1, 3],
        //          [1, 2, 3],
        //          [2, 2, 3],
        //          [3, 2, 3],
        //          [1, 3, 3],
        //          [2, 3, 3],
        //          [3, 3, 3]
        //        ]
        private static IEnumerable<int[]> GenerateCombinations(int[] options, int count)
        {
            int[] indexTracker = new int[count];
            int[] combo = new int[count];
            for (int i = 0; i < count; ++i)
            {
                combo[i] = options[0];
            }
            // Same algorithm as picking a combination lock.
            int rollovers = 0;
            while (rollovers < count)
            {
                yield return combo; // No need to duplicate the array since we're just reading it.
                for (int i = 0; i < count; ++i)
                {
                    int index = ++indexTracker[i];
                    if (index == options.Length)
                    {
                        indexTracker[i] = 0;
                        combo[i] = options[0];
                        if (i == rollovers)
                        {
                            ++rollovers;
                        }
                    }
                    else
                    {
                        combo[i] = options[index];
                        break;
                    }
                }
            }
        }
    }
}

使用示例:

[Test]
public void DeferredMayBeBeResolvedAndPromiseAwaitedConcurrently_void0()
{
    Promise.Deferred deferred = default(Promise.Deferred);
    Promise promise = default(Promise);

    int invokedCount = 0;

    var threadHelper = new ThreadHelper();
    threadHelper.ExecuteParallelActionsWithOffsets(false,
        // Setup
        () =>
        {
            invokedCount = 0;
            deferred = Promise.NewDeferred();
            promise = deferred.Promise;
        },
        // Teardown
        () => Assert.AreEqual(1, invokedCount),
        // Parallel Actions
        () => deferred.Resolve(),
        () => promise.Then(() => { Interlocked.Increment(ref invokedCount); }).Forget()
    );
}

一个简单的测试模式可以用于一些(不是所有!)用例，就是多次重复相同的测试。例如，假设你有一个方法:

def process(input):
    # Spawns several threads to do the job
    # ...
    return output

创建一堆测试:

process(input1) -> expect to return output1
process(input2) -> expect to return output2
...

现在将每个测试运行多次。

如果流程的实现包含一个微小的错误(例如死锁、竞态条件等)，出现的概率为0.1%，那么运行1000次测试，则该错误至少出现一次的概率为64%。运行测试10000次，得到>99%的概率。

您可以使用EasyMock。使测试实例线程安全

Pete Goodliffe有一个关于线程代码单元测试的系列。

是很困难的。我采用了更简单的方法，尽量将线程代码从实际测试中抽象出来。皮特确实提到了我分手的方式是错误的但我要么是正确的，要么就是我很幸运。

上周我花了大部分时间在大学图书馆学习并发代码的调试。核心问题是并发代码是不确定的。通常，学术调试可以分为三个阵营之一:

Event-trace/replay. This requires an event monitor and then reviewing the events that were sent. In a UT framework, this would involve manually sending the events as part of a test, and then doing post-mortem reviews. Scriptable. This is where you interact with the running code with a set of triggers. "On x > foo, baz()". This could be interpreted into a UT framework where you have a run-time system triggering a given test on a certain condition. Interactive. This obviously won't work in an automatic testing situation. ;)

现在，正如上面评论者所注意到的，您可以将并发系统设计成更确定的状态。然而，如果你做得不好，你就又回到了设计顺序系统的问题上。

我的建议是，专注于制定一个非常严格的设计协议，规定什么是线程，什么不是线程。如果你限制了你的接口，使元素之间的依赖最小化，那就容易多了。

祝你好运，继续解决这个问题。

对于Java，请参阅JCIP的第12章。有一些具体的例子，可以编写确定性的多线程单元测试，以至少测试并发代码的正确性和不变量。

用单元测试“证明”线程安全要危险得多。我相信在各种平台/配置上进行自动化集成测试会更好。