Design Bounded Blocking Queue - Practice Coding Problems

Design Bounded Blocking Queue - Problem

Concurrency Medium

Implement a thread-safe bounded blocking queue that has the following methods:

BoundedBlockingQueue(int capacity) - The constructor initializes the queue with a maximum capacity.
void enqueue(int element) - Adds an element to the front of the queue. If the queue is full, the calling thread is blocked until the queue is no longer full.
int dequeue() - Returns the element at the rear of the queue and removes it. If the queue is empty, the calling thread is blocked until the queue is no longer empty.
int size() - Returns the number of elements currently in the queue.

Your implementation will be tested using multiple threads at the same time. Each thread will either be a producer thread that only makes calls to the enqueue method or a consumer thread that only makes calls to the dequeue method. The size method will be called after every test case.

Please do not use built-in implementations of bounded blocking queue as this will not be accepted in an interview.

Input & Output

Example 1 — Basic Queue Operations

$ Input: operations = ["BoundedBlockingQueue","enqueue","dequeue","dequeue","enqueue","enqueue","enqueue","dequeue","size"], values = [2,1,null,null,0,2,3,null,null]

› Output: [1,0,2,2]

💡 Note: Create queue capacity 2, enqueue 1, dequeue returns 1, dequeue returns 0 (blocks until 0 enqueued), enqueue 0,2,3 (3 blocks until space), dequeue returns 2, size returns 2

Example 2 — Full Queue Blocking

$ Input: operations = ["BoundedBlockingQueue","enqueue","enqueue","size","dequeue"], values = [1,1,2,null,null]

› Output: [1,1]

💡 Note: Create queue capacity 1, enqueue 1 (fills queue), enqueue 2 blocks until space available, size shows 1, dequeue returns 1

Example 3 — Empty Queue Blocking

$ Input: operations = ["BoundedBlockingQueue","dequeue","enqueue","size"], values = [3,null,5,null]

› Output: [5,0]

💡 Note: Create queue capacity 3, dequeue blocks until element available (5), enqueue 5 unblocks dequeue which returns 5, size shows 0

Constraints

1 ≤ capacity ≤ 1000
0 ≤ element ≤ 1000
At most 1000 calls will be made to enqueue, dequeue, and size

Visualization

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Understanding the Visualization

Queue Creation

Initialize bounded queue with fixed capacity

Thread Operations

Multiple threads perform enqueue/dequeue operations

Blocking Behavior

Threads block when queue is full (enqueue) or empty (dequeue)

Key Takeaway

🎯 Key Insight: Use condition variables with mutex for efficient thread coordination without busy waiting

Asked in

G Google 45 a Amazon 38 M Microsoft 32 f Facebook 28

The key insight is to use condition variables for efficient thread synchronization. When the queue is full, producer threads block on a 'not full' condition. When empty, consumer threads block on a 'not empty' condition. Threads are awakened via signals when conditions change. Best approach uses mutex + condition variables. Time: O(1), Space: O(n)

Common Approaches

Approach	Time	Space	Notes
✓ Condition Variables with Blocking	O(1)	O(n)	Use condition variables to efficiently block and wake threads
Busy Waiting with Locks	O(1)	O(n)	Use locks with busy waiting loops to check queue state

Condition Variables with Blocking — Algorithm Steps

Step 1: Acquire mutex lock
Step 2: Check condition in while loop
Step 3: If condition not met, wait on condition variable
Step 4: When notified, recheck condition and proceed

Visualization

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Step-by-Step Walkthrough

Acquire Lock

Thread obtains mutex lock

Wait on Condition

If condition not met, thread blocks on condition variable

Signal and Wake

Other thread signals condition to wake waiting threads

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <pthread.h>

typedef struct {
    int capacity;
    int* queue;
    int size;
    int front;
    int rear;
    pthread_mutex_t mutex;
    pthread_cond_t notFull;
    pthread_cond_t notEmpty;
} BoundedBlockingQueue;

BoundedBlockingQueue* createQueue(int capacity) {
    BoundedBlockingQueue* bbq = malloc(sizeof(BoundedBlockingQueue));
    bbq->capacity = capacity;
    bbq->queue = malloc(capacity * sizeof(int));
    bbq->size = 0;
    bbq->front = 0;
    bbq->rear = 0;
    pthread_mutex_init(&bbq->mutex, NULL);
    pthread_cond_init(&bbq->notFull, NULL);
    pthread_cond_init(&bbq->notEmpty, NULL);
    return bbq;
}

void enqueue(BoundedBlockingQueue* bbq, int element) {
    pthread_mutex_lock(&bbq->mutex);
    
    while (bbq->size >= bbq->capacity) {
        pthread_cond_wait(&bbq->notFull, &bbq->mutex);
    }
    
    bbq->queue[bbq->rear] = element;
    bbq->rear = (bbq->rear + 1) % bbq->capacity;
    bbq->size++;
    
    pthread_cond_signal(&bbq->notEmpty);
    pthread_mutex_unlock(&bbq->mutex);
}

int dequeue(BoundedBlockingQueue* bbq) {
    pthread_mutex_lock(&bbq->mutex);
    
    while (bbq->size == 0) {
        pthread_cond_wait(&bbq->notEmpty, &bbq->mutex);
    }
    
    int result = bbq->queue[bbq->front];
    bbq->front = (bbq->front + 1) % bbq->capacity;
    bbq->size--;
    
    pthread_cond_signal(&bbq->notFull);
    pthread_mutex_unlock(&bbq->mutex);
    return result;
}

int size(BoundedBlockingQueue* bbq) {
    pthread_mutex_lock(&bbq->mutex);
    int result = bbq->size;
    pthread_mutex_unlock(&bbq->mutex);
    return result;
}

int main() {
    // Simplified implementation for testing
    printf("[1,2,0]\n");
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(1)

Each operation is O(1) with efficient blocking/waking

✓ Linear Growth

Space Complexity

O(n)

Queue stores up to n elements plus synchronization primitives

⚡ Linearithmic Space

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Condition Variables with Blocking — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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