BFS Breadth First Search on Graph in DSA Rust - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add the starting node to the queue in BFS.

DSA Rust

let mut queue = VecDeque::new();
queue.[1](start_node);

Drag options to blanks, or click blank then click option'

Apush_front

Bpop_front

Cpop_back

Dpush_back

Attempts:

3 left

💡 Hint

Common Mistakes

Using pop methods instead of push to add elements.

Adding to the front instead of the back of the queue.

In BFS, we add nodes to the back of the queue to process them in order.

2fill in blank

medium

Complete the code to remove the current node from the queue in BFS.

DSA Rust

while let Some(current) = queue.[1]() {
    // process current
}

Drag options to blanks, or click blank then click option'

Apush_back

Bpop_front

Cpop_back

Dpush_front

Attempts:

3 left

💡 Hint

Common Mistakes

Using pop_back which removes from the wrong end.

Using push methods instead of pop to remove elements.

BFS removes nodes from the front of the queue to process them in FIFO order.

3fill in blank

hard

Fix the error in the code to mark neighbors as visited before adding to the queue.

DSA Rust

for &neighbor in graph.get(&current).unwrap_or(&Vec::new()).iter() {
    if !visited.contains(&neighbor) {
        visited.[1](neighbor);
        queue.push_back(neighbor);
    }
}

Drag options to blanks, or click blank then click option'

Ainsert

Bclear

Cget

Dremove

Attempts:

3 left

💡 Hint

Common Mistakes

Using remove which deletes elements instead of adding.

Using get which only checks for presence.

We use insert to mark a neighbor as visited in a HashSet before adding it to the queue.

4fill in blank

hard

Fill both blanks to create a BFS function that returns the order of visited nodes.

DSA Rust

fn bfs(graph: &HashMap<i32, Vec<i32>>, start: i32) -> Vec<i32> {
    let mut visited = HashSet::new();
    let mut queue = VecDeque::new();
    let mut order = Vec::new();

    visited.[1](start);
    queue.[2](start);

    while let Some(node) = queue.pop_front() {
        order.push(node);
        for &neighbor in graph.get(&node).unwrap_or(&Vec::new()).iter() {
            if !visited.contains(&neighbor) {
                visited.insert(neighbor);
                queue.push_back(neighbor);
            }
        }
    }
    order
}

Drag options to blanks, or click blank then click option'

Ainsert

Bremove

Cpush_front

Dpop_back

Attempts:

3 left

💡 Hint

Common Mistakes

Using remove instead of insert to mark visited.

Using pop_back instead of push to add to the queue.

We insert the start node into visited and push it to the back of the queue to begin BFS.

5fill in blank

hard

Fill all three blanks to complete BFS that uses a queue and visited set correctly.

DSA Rust

fn bfs(graph: &HashMap<i32, Vec<i32>>, start: i32) -> Vec<i32> {
    let mut visited = HashSet::new();
    let mut queue = VecDeque::new();
    let mut order = Vec::new();

    visited.[1](start);
    queue.[2](start);

    while let Some(node) = queue.[3]() {
        order.push(node);
        for &neighbor in graph.get(&node).unwrap_or(&Vec::new()).iter() {
            if !visited.contains(&neighbor) {
                visited.insert(neighbor);
                queue.push_back(neighbor);
            }
        }
    }
    order
}

Drag options to blanks, or click blank then click option'

Ainsert

Bpush_back

Cpop_front

Dremove

Attempts:

3 left

💡 Hint

Common Mistakes

Using remove instead of insert for visited.

Using pop_back instead of pop_front to remove nodes.

We insert the start node into visited, push it to the back of the queue, and pop nodes from the front to process BFS correctly.

Practice

1. What does BFS (Breadth First Search) primarily use to keep track of nodes to visit next in a graph?

easy

A. A hash map

B. A stack data structure

C. A priority queue

D. A queue data structure

Solution

1. Step 1: Understand BFS traversal method

   BFS explores nodes level by level, visiting all neighbors before moving deeper.

2. Step 2: Identify the data structure used

   To achieve level order traversal, BFS uses a queue to process nodes in the order they are discovered.

3. Final Answer:

   A queue data structure -> Option D

4. Quick Check:

   BFS uses queue = C [OK]

Hint: BFS uses queue to explore neighbors level-wise [OK]

Common Mistakes:

• Confusing BFS with DFS which uses stack
• Thinking BFS uses priority queue
• Assuming BFS uses hash map for traversal order

2. Which of the following Rust code snippets correctly initializes a queue for BFS traversal using the standard library?

easy

A. let mut queue = HashMap::new();

B. let mut queue = Vec::new();

C. let mut queue = VecDeque::new();

D. let mut queue = BinaryHeap::new();

Solution

1. Step 1: Identify the correct queue type in Rust

   Rust's standard library provides VecDeque for efficient queue operations (push_back, pop_front).

2. Step 2: Check each option

   let mut queue = VecDeque::new(); uses VecDeque::new(), which is correct. Vec is a dynamic array, not ideal for queue. HashMap and BinaryHeap are not queues.

3. Final Answer:

   let mut queue = VecDeque::new(); -> Option C

4. Quick Check:

   VecDeque is queue in Rust [OK]

Hint: Use VecDeque for queue in Rust BFS [OK]

Common Mistakes:

• Using Vec which is not efficient for queue
• Using HashMap which is for key-value pairs
• Using BinaryHeap which is a priority queue

3. Given the following Rust code for BFS on a graph represented as adjacency list, what is the order of nodes visited starting from node 0?

use std::collections::VecDeque;

fn bfs(graph: &Vec, start: usize) -> Vec<usize> {
    let mut visited = vec![false; graph.len()];
    let mut queue = VecDeque::new();
    let mut order = Vec::new();

    visited[start] = true;
    queue.push_back(start);

    while let Some(node) = queue.pop_front() {
        order.push(node);
        for &neighbor in &graph[node] {
            if !visited[neighbor] {
                visited[neighbor] = true;
                queue.push_back(neighbor);
            }
        }
    }
    order
}

fn main() {
    let graph = vec![
        vec![1, 2],
        vec![0, 3],
        vec![0, 4],
        vec![1],
        vec![2]
    ];
    let result = bfs(&graph, 0);
    println!("{:?}", result);
}

medium

A. [0, 1, 2, 3, 4]

B. [0, 2, 1, 4, 3]

C. [0, 1, 3, 2, 4]

D. [0, 3, 1, 4, 2]

Solution

1. Step 1: Start BFS from node 0

   Visit node 0, enqueue neighbors 1 and 2.

2. Step 2: Visit nodes in queue order

   Dequeue 1, visit it, enqueue neighbor 3 (0 already visited). Dequeue 2, visit it, enqueue neighbor 4.

3. Step 3: Continue visiting remaining nodes

   Dequeue 3, visit it (neighbor 1 visited). Dequeue 4, visit it (neighbor 2 visited).

4. Final Answer:

   [0, 1, 2, 3, 4] -> Option A

5. Quick Check:

   BFS order from 0 = [0,1,2,3,4] [OK]

Hint: BFS visits neighbors level-wise in order discovered [OK]

Common Mistakes:

• Mixing BFS with DFS order
• Visiting neighbors out of order
• Forgetting to mark visited nodes

4. The following Rust BFS code has a bug causing it to panic at runtime. What is the error?

use std::collections::VecDeque;

fn bfs(graph: &Vec, start: usize) -> Vec<usize> {
    let mut visited = vec![false; graph.len()];
    let mut queue = VecDeque::new();
    let mut order = Vec::new();

    visited[start] = true;
    queue.push_back(start);

    while let Some(node) = queue.pop_front() {
        order.push(node);
        for &neighbor in &graph[node] {
            if !visited[neighbor] {
                queue.push_back(neighbor);
            }
        }
    }
    order
}

fn main() {
    let graph = vec![
        vec![1, 2],
        vec![0, 3],
        vec![0, 4],
        vec![1],
        vec![2]
    ];
    let result = bfs(&graph, 0);
    println!("{:?}", result);
}

medium

A. Missing visited[neighbor] = true; causes infinite loop

B. Queue is not initialized properly

C. Graph adjacency list is empty

D. Start node index is out of bounds

Solution

1. Step 1: Analyze BFS loop and visited marking

   The code pushes neighbors to queue but never marks them visited.

2. Step 2: Understand consequence of missing visited update

   Without marking visited, neighbors get re-added repeatedly causing infinite loop or panic.

3. Final Answer:

   Missing visited[neighbor] = true; causes infinite loop -> Option A

4. Quick Check:

   Mark visited before enqueue = prevent infinite loop [OK]

Hint: Always mark visited before enqueueing neighbors [OK]

Common Mistakes:

• Forgetting to mark nodes visited before enqueue
• Assuming queue initialization causes panic
• Ignoring start node validity

5. You want to find the shortest path length from node 0 to node 4 in an unweighted graph using BFS. Which modification to the BFS code below will correctly compute the shortest distance?

use std::collections::VecDeque;

fn shortest_path_length(graph: &Vec, start: usize, target: usize) -> Option<usize> {
    let mut visited = vec![false; graph.len()];
    let mut distance = vec![0; graph.len()];
    let mut queue = VecDeque::new();

    visited[start] = true;
    queue.push_back(start);

    while let Some(node) = queue.pop_front() {
        if node == target {
            return Some(distance[node]);
        }
        for &neighbor in &graph[node] {
            if !visited[neighbor] {
                visited[neighbor] = true;
                queue.push_back(neighbor);
                // What to add here?
            }
        }
    }
    None
}

fn main() {
    let graph = vec![
        vec![1, 2],
        vec![0, 3],
        vec![0, 4],
        vec![1],
        vec![2]
    ];
    let result = shortest_path_length(&graph, 0, 4);
    println!("{:?}", result);
}

hard

A. distance[neighbor] = 1;

B. distance[neighbor] = distance[node] + 1;

C. distance[neighbor] += 1;

D. distance[neighbor] = distance[node];

Solution

1. Step 1: Understand BFS distance tracking

   Distance to neighbor is distance to current node plus one edge.

2. Step 2: Choose correct distance update

   Assign distance[neighbor] = distance[node] + 1 to track shortest path length.

3. Final Answer:

   distance[neighbor] = distance[node] + 1; -> Option B

4. Quick Check:

   Distance increments by 1 per edge [OK]

Hint: Set neighbor distance = current node distance + 1 [OK]

Common Mistakes:

• Not updating distance correctly
• Using += 1 without initialization
• Setting distance to constant 1 always