As experts in the field of computer science, we understand the challenges students face when tackling complex programming assignments. At ProgrammingHomeworkHelp.com, we specialize in providing top-tier assistance, ensuring students grasp intricate concepts while excelling academically. If you are looking for programming assignment help USA, our expert solutions can guide you toward mastering advanced topics. Below, we present two challenging master-level programming questions along with their comprehensive solutions.

Question: Implement a thread-safe queue in Python that allows multiple producer and consumer threads to access it concurrently. The implementation should include proper synchronization mechanisms to avoid race conditions and ensure safe data access.

Solution:

import threadingfrom queue import Queueclass ThreadSafeQueue:    def __init__(self):        self.queue = Queue()        self.lock = threading.Lock()        def enqueue(self, item):        with self.lock:            self.queue.put(item)        def dequeue(self):        with self.lock:            if not self.queue.empty():                return self.queue.get()            return None# Example usage with multiple threadsdef producer(q, items):    for item in items:        q.enqueue(item)        print(f"Produced: {item}")def consumer(q, count):    for _ in range(count):        item = q.dequeue()        if item is not None:            print(f"Consumed: {item}")queue = ThreadSafeQueue()producer_thread = threading.Thread(target=producer, args=(queue, range(5)))consumer_thread = threading.Thread(target=consumer, args=(queue, 5))producer_thread.start()consumer_thread.start()producer_thread.join()consumer_thread.join()

Explanation:

• A queue from Python’s queue module ensures thread safety.

• A lock synchronizes access, preventing race conditions.

• The producer thread adds items, and the consumer thread retrieves them in a synchronized manner.

Question: Develop a C++ program that simulates memory allocation using a buddy system. The program should allow memory requests and deallocation, efficiently managing memory blocks.

Solution:

#include iostream#include map#include cmathclass BuddyAllocator {private:    std::mapint, bool memoryBlocks; // Key: block size, Value: availability    int totalMemory;    public:    BuddyAllocator(int size) : totalMemory(size) {        memoryBlocks[size] = true;    }        int allocate(int size) {        for (auto block : memoryBlocks) {            if (block.first = size  block.second) {                block.second = false;                return block.first;            }        }        return -1; // No suitable block found    }        void deallocate(int size) {        memoryBlocks[size] = true;    }        void display() {        for (const auto block : memoryBlocks) {            std::cout  "Block Size: "  block.first  " | Available: "  block.second  std::endl;        }    }};int main() {    BuddyAllocator allocator(1024);    int allocated = allocator.allocate(256);    if (allocated != -1)        std::cout  "Allocated block of size: "  allocated  std::endl;    allocator.display();    allocator.deallocate(256);    allocator.display();    return 0;}

Explanation:

• A buddy system is implemented using a map to store memory blocks and their availability.

• The allocate function finds the smallest suitable block and marks it as used.

• The deallocate function frees up memory when needed.

• The display function showcases the memory status.

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