hints.md

Hints for Concurrent Graph BFS Queries

Hint 1: Worker Pool Pattern

You need to implement a worker pool pattern. Create numWorkers goroutines that will process BFS queries from a channel:

jobs := make(chan int, len(queries))
results := make(chan BFSResult, len(queries))

Hint 2: BFS Result Structure

Define a struct to hold BFS results:

type BFSResult struct {
    StartNode int
    Order     []int
}

Hint 3: Starting Workers

Launch the specified number of worker goroutines:

for i := 0; i < numWorkers; i++ {
    go worker(graph, jobs, results)
}

Hint 4: Sending Jobs

Send all queries to the jobs channel and close it:

for _, query := range queries {
    jobs <- query
}
close(jobs)

Hint 5: Standard BFS Implementation

Each worker performs standard BFS using a queue:

func bfs(graph map[int][]int, start int) []int {
    visited := make(map[int]bool)
    queue := []int{start}
    order := []int{}
    // ... implement BFS
}

Hint 6: Worker Function Structure

The worker function should process jobs until the channel is closed:

func worker(graph map[int][]int, jobs <-chan int, results chan<- BFSResult) {
    for start := range jobs {
        order := bfs(graph, start)
        results <- BFSResult{StartNode: start, Order: order}
    }
}

Hint 7: Collecting Results

Collect all results and convert to the required map format:

resultMap := make(map[int][]int)
for i := 0; i < len(queries); i++ {
    result := <-results
    resultMap[result.StartNode] = result.Order
}

Hint 8: BFS Queue Operations

For BFS, use slice operations for queue:

// Dequeue (remove from front)
node := queue[0]
queue = queue[1:]

// Enqueue (add to back)
queue = append(queue, neighbor)