避免非托管C ++，C ++ / CLI和C＃代码之间的std :: deque迭代器不可解除错误

Question

我有一个VS2015解决方案，其中包括不受管理的c ++代码（以执行一些CPU密集型模拟计算），围绕此代码的c ++ / cli包装器以及ac＃项目，该项目通过DLL调用c ++ / cli包装器。 下面的示例是完整代码的简化版本，对于预先提供的代码数量感到抱歉，但是对于所发生的情况的完整了解是必需的。

非托管C ++代码

class diffusion_limited_aggregate {
public:
    diffusion_limited_aggregate() 
        : aggregate_map(), attractor_set(), batch_queue() {}
    std::size_t size() const noexcept { return aggregate_map.size(); }
    std::queue<std::pair<int,int>>& batch_queue_handle() noexcept { return batch_queue; }
    void generate(std::size_t n) {
        initialise_attractor_structure(); // set up initial attractor seed points
        std::size_t count = 0U;
        std::pair<int,int> current = std::make_pair(0,0);
        std::pair<int,int> prev = current;
        bool has_next_spawned = false;
        while (size() < n) {
            if (!has_next_spawned) {
                // => call function to spawn particle setting current 
                has_next_spawned = true;
            }
            prev = current;
            // => call function to update random walking particle position
            // => call function to check for lattice boundary collision
            if (aggregate_collision(current, prev, count)) has_next_spawned = false;
        }
    }
    void initialise_attractor_structure() {
        attractor_set.clear();
        attractor_set.insert(std::make_pair(0,0));
    }
    void push_particle(const std::pair<int,int>& p, std::size_t count) {
        aggregate_map.insert(std::make_pair(p, count));
        batch_queue.push(p);
    }
    bool aggregate_collision(const std::pair<int,int>& current,
        const std::pair<int,int>& prev, std::size_t& count) {
        if (aggregate_map.find(current) != aggregate_map.end() 
            || attractor_set.find(current) != attractor_set.end()) {
            push_particle(previous, ++count);
            return true;
        }
        return false;
    }
private:
    std::unordered_map<std::pair<int,int>, 
        std::size_t,
        utl::tuple_hash> aggregate_map;
    std::unordered_set<std::pair<int,int>, utl::tuple_hash> attractor_set;
    std::queue<std::pair<int,int>> batch_queue; // holds buffer of aggregate points
};

其中utl::tuple_hash是std::pair的哈希函数对象，更一般而言，是std::tuple实例的哈希函数对象，定义为：

namespace utl {
    template<class Tuple, std::size_t N>
    struct tuple_hash_t {
        static std::size_t tuple_hash_compute(const Tuple& t) {
            using type = typename std::tuple_element<N-1, Tuple>::type;
            return tuple_hash_t<Tuple,N-1>::tuple_hash_compute(t)
                + std::hash<type>()(std::get<N-1>(t));
        }
    };
    // base
    template<class Tuple>
    struct tuple_hash_t<Tuple, 1> {
        static std::size_t tuple_hash_compute(const Tuple& t) {
            using type = typename std::tuple_element<0,Tuple>::type;
            return 51U + std::hash<type>()(std::get<0>(t))*51U;
        }
    };
    struct tuple_hash {
        template<class... Args>
        std::size_t operator()(const std::tuple<Args...>& t) const {
            return tuple_hash_t<std::tuple<Args...>,sizeof...(Args)>::tuple_hash_compute(t);
        }
        template<class Ty1, class Ty2>
        std::size_t operator()(const std::pair<Ty1, Ty2>& p) const {
            return tuple_hash_t<std::pair<Ty1,Ty2>,2>::tuple_hash_compute(p);
        }
    };
}

---

托管C ++ / CLI包装器

以下是在围绕类C ++ / CLI的包装diffusion_limited_aggregate ，在这种情况下，重要的方法是ProcessBatchQueue 。 此方法是必须发生std::deque iterator not dereferencable error的地方，因为它是访问并弹出batch_queue内容的唯一位置。

public ref class ManagedDLA2DContainer {
private:
    diffusion_limited_aggregate* native_dla_2d_ptr;
    System::Object^ lock_obj = gcnew System::Object();
public:
    ManagedDLA2DContainer() : native_dla_2d_ptr(new diffusion_limited_aggregate()) {}
    ~ManagedDLA2DContainer() { delete native_dla_2d_ptr; }
    std::size_t Size() { return native_dla_2d_ptr->size(); }
    void Generate(std::size_t n) { native_dla_2d_ptr->generate(n); }
    System::Collections::Concurrent::BlockingCollection<
        System::Collections::Generic::KeyValuePair<int,int>
    >^ ProcessBatchQueue() {
        // store particles in blocking queue configuration
        System::Collections::Concurrent::BlockingCollection<
            System::Collections::Generic::KeyValuePair<int,int>>^ blocking_queue =
            gcnew System::Collections::Concurrent::BlockingCollection<
                System::Collections::Generic::KeyValuePair<int,int>
            >();
        System::Threading::Monitor::Enter(lock_obj); // define critical section start
        try {
            // get ref to batch_queue
            std::queue<std::pair<int,int>>& bq_ref = native_dla_2d_ptr->batch_queue_handle();
            // loop over bq transferring particles to blocking_queue
            while (!bq_ref.empty()) {
                auto front = std::move(bq_ref.front());
                blocking_queue->Add(System::Collections::Generic::KeyValuePair<int,int>(front.first,front.second));
                bq_ref.pop();
            }
        }
        finally { System::Threading::Monitor::Exit(lock_obj); }
        return blocking_queue;
    }
}

---

C＃代码

最后，我有以下c＃代码，该代码使用ManagedDLA2DContainer生成聚合并将其显示在界面上。

public partial class MainWindow : Window {
    private static readonly System.object locker = new object();
    private readonly ManagedDLA2DContainer dla_2d;
    public MainWindow() {
        InitializeComponent();
        dla_2d = new ManagedDLA2DContainer();
    }
    private void GenerateAggregate(uint n) {
        // start asynchronous task to perform aggregate simulation computations
        Task.Run(() => CallNativeCppAggregateGenerators(n));
        System.Threading.Thread.Sleep(5);
        // start asynchronous task to perform rendering
        Task.Run(() => AggregateUpdateListener(n));
    }
    private void CallNativeCppAggregateGenerators(uint n) {
        dla_2d.Generate(n);
    }
    private void AggregateUpdateListener(uint n) {
        const double interval = 10.0;
        Timer timer = new Timer(interval);
        timer.Elapsed += Update2DAggregateOnTimedEvent;
        timer.AutoReset = true;
        timer.Enabled = true;
    }
    private void Update2DAggregateOnTimedEvent(object source, ElapsedEventArgs e) {
        lock(locker) {
            BlockingCollection<KeyValuePair<int,int>> bq = dla_2d.ProcessBatchQueue();
            while(bq.Count != 0) {
                KeyValuePair<int,int> p = bq.Take();
                Point3D pos = new Point3D(p.Key, p.Value, 0.0);
                // => do stuff with pos, sending to another class method for rendering
                // using Dispatcher.Invoke(() => { ... }); to render in GUI
            }
        }
    }
}

该方法GenerateAggregate只叫每个聚集执行一次，它是通过一个按钮处理程序方法被称为我有一个Generate带有该接口上的方法OnGenerateButtonClicked它调用的事件处理函数GenerateAggreate 。 在代码中的其他任何地方， CallNativeCppAggregateGenerators和AggregateUpdateListener均未调用。

---

问题

如托管包装部分所述，执行此代码时，我偶尔会收到运行时断言错误，

std::deque迭代器不可取消。

这通常在首次执行时发生，但也确实在正在进行的聚合生成过程的中间发生，因此，生成聚合的启动代码在这里可能不是罪魁祸首。

我该如何解决这个问题？ 希望这是我的关键部分代码或类似代码中出现逻辑错误的简单情况，但是我还无法查明确切的问题。

如评论中所指出的那样，问题可能是元素不断被添加batch_queue而调用ProcessBatchQueue的C＃线程正在使用队列元素，从而可能会使batch_queue的迭代器无效。 是否有可应用于此用例的典型生产者-消费者设计模式？

编辑：如果下降投票者可以给出他们的理由，这样我可以改善这个问题，那就太好了。

Answer 1

我为这个问题找到了解决方案，下面将详细介绍。 如问题中所建议的那样，问题在于，在处理batch_queue时，由于在聚合生成过程中将元素连续推入队列，其迭代器有时会失效。

该解决方案比以前的基于batch_queue的实现使用更多的内存，但是就迭代器的有效性而言，它是安全的。 我用本地c ++代码中的聚合粒子的std::vector<std::pair<int,int>>缓冲区替换了batch_queue ：

class diffusion_limited_aggregate {
public:
//...
    const std::vector<std::pair<int,int>>& aggregate_buffer() const noexcept { return buffer; }
private:
//...
    std::vector<std::pair<int,int>> buffer;
};

然后，将ManagedDLA2DContainer::ProcessBatchQueue替换为ManagedDLA2DContainer::ConsumeBuffer ，该ManagedDLA2DContainer::ConsumeBuffer读取标记的索引并将最新一批的聚集粒子推入ac＃ List<KeyValuePair<int,int>> ：

System::Collections::Generic::List<System::Collections::Generic::KeyValuePair<int, int>>^ ConsumeBuffer(std::size_t marked_index) {
        System::Collections::Generic::List<System::Collections::Generic::KeyValuePair<int, int>>^ buffer =
            gcnew System::Collections::Generic::List<System::Collections::Generic::KeyValuePair<int, int>>();
        if (native_dla_2d_ptr->aggregate_buffer().empty()) return buffer;
        System::Threading::Monitor::Enter(lock_obj);    // define critical section start
        try {   // execute critical section
            // read from last marked buffer index up to size of buffer and write these data to batch list
            for (int i = marked_index; i < native_dla_2d_ptr->aggregate_buffer().size(); ++i) {
                buffer->Add(System::Collections::Generic::KeyValuePair<int, int>(
                    native_dla_2d_ptr->aggregate_buffer()[i].first,
                    native_dla_2d_ptr->aggregate_buffer()[i].second
                    )
                );
            }
        }
        finally { System::Threading::Monitor::Exit(lock_obj); } // exit critical section by releasing exclusive lock
        return buffer;
}

最后，更改了c＃ MainWindow::Update2DAggregateOnTimedEvent方法中的代码，以反映c ++ / cli代码中的这些更改：

private void Update2DAggregateOnTimedEvent(object source, ElapsedEventArgs e, uint n) {
    lock (locker) {
        List<KeyValuePair<int,int>> buffer = dla_2d.ConsumeBuffer(
            (current_particles == 0) ? 0 : current_particles-1); // fetch batch list
        foreach (var p in buffer) {
            // => add p co-ords to GUI manager...
            ++current_particles;
            // => render aggregate...
        }
    }
}