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Free lesson walkthrough · TypeScript

BFS shortest path in TypeScript: Pilot a Rocket

Find an unweighted shortest route and reconstruct it from predecessor links. Follow the TypeScript implementation, its correctness argument, worked example, complexity, and boundary tests.

4 min read · Worked code, edge cases, and complexity

Find a shortest route from the vertex named base to the vertex named ship in an unweighted adjacency map. Return the vertex names in route order, including both endpoints. If no route exists, return null rather than an empty route. Every referenced neighbor has an entry in the supplied graph, and the route follows the listed edge directions.

Explore routes in increasing edge count

Breadth-first search uses a first-in, first-out queue. Start by enqueuing base. When removing a vertex, enqueue each neighbor that has not already been discovered. All vertices one edge from the start are discovered before vertices two edges away, and so on. The first discovery of a vertex therefore uses a shortest route to it.

Keep a predecessor map. Set the start's predecessor to an absence sentinel and record each newly discovered neighbor's predecessor as the current vertex. The map also serves as the discovered set. Record a neighbor before enqueueing it, so several incoming edges cannot add it to the queue repeatedly.

Reconstruct one route

Suppose base connects to a and b, a connects to c, b connects to ship, and c also connects to ship. Breadth-first search discovers a and b at distance one. Processing b discovers ship at distance two, before the route through a and c can improve anything. Its predecessor chain is ship, b, base.

Follow that chain backward from ship until the start sentinel, collect the names, then reverse the collection. The result is [base, b, ship]. Keeping only a visited set would establish reachability but would lose the information needed to return the route. Storing a full route in every queue item is possible, but copies many shared prefixes.

Preserve the shortest-route guarantee

The queue processes vertices in nondecreasing distance from base. When a vertex is first discovered from a distance-d predecessor, it gets distance d + 1. Any shorter predecessor would already have been processed and discovered it earlier. The recorded predecessor thus belongs to a shortest route.

Cycles do not break termination because each vertex is discovered once. A self-loop on base sees the existing start entry and adds nothing. If the queue empties without finding ship, every reachable vertex has been explored, proving that no route exists. Several equal-length routes may exist; adjacency order selects one unless the contract supplies a tie rule.

Inspect the queue implementation's cost

The graph algorithm examines O(V + E) reachable vertices and edges when queue operations take amortized O(1) time. A queue implemented with front insertion or removal on an array can move all its elements on each operation, adding O(V²) work in a wide search. A head index, deque, or linked queue avoids that repeated shifting.

The queue and predecessor map use O(V) storage. Reconstructing a route costs time and output space proportional to its length. String-key hashing also depends on identifier lengths. The unweighted assumption matters: breadth-first search minimizes edge count, not a sum of arbitrary fuel costs or travel durations.

Test reachability and route validity

Test a direct base-to-ship edge, an unreachable ship, a cycle, a self-loop, and a tempting longer route listed before a shorter one. Include branching paths with a shared destination to check discovery-time deduplication. Verify that every adjacent pair in the returned route is an edge and that the endpoints are correct.

For generated checks, compute shortest distances independently and require the returned route length to equal the minimum distance plus one. If exact output order is required, make the shortest route unique or specify the tie behavior. A weighted follow-up needs an algorithm such as Dijkstra's for nonnegative weights; changing the queue order alone without distance relaxation does not establish correctness.

TypeScript implementation

The predecessor table distinguishes an undiscovered key from the start’s null predecessor. That distinction also prevents revisiting the start through a cycle.

The TypeScript annotations describe the course input contract; they do not validate arbitrary JSON at runtime. Numeric values use JavaScript numbers, including the same safe integer limit. Array and object mutations are visible through shared references. Keep the declared entry name and return shape when moving the implementation into the lesson editor.

interface Satellites {
  [key: string]: string[];
}

interface PreviousNodeMap {
  [key: string]: string | null;
}

const START_NODE = 'base';
const END_NODE = 'ship';

function pilotRocket(satellites: Satellites): string[] | null {
  // Queue to handle BFS
  const bfsNodeQueue = new Queue();
  bfsNodeQueue.enqueue(START_NODE);

  // Use a hash table to track the node that came
  // prior to the current in our BFS to track the path
  const previousNodeInPath = {};
  previousNodeInPath[START_NODE] = null;

  // Perform our BFS
  while (bfsNodeQueue.size() > 0) {
    const node = bfsNodeQueue.dequeue();

    // We've successfully reached the end, and now we should build the path to get here
    if (node === END_NODE) {
      return getShortestPathToShip(previousNodeInPath);
    }

    for (let connectedNode of satellites[node]) {
      // Check if we have visited this node yet
      if (previousNodeInPath[connectedNode] === undefined) {

        // Add the node to the queue for our BFS
        bfsNodeQueue.enqueue(connectedNode);

        // Set the current node as the one that came before each of its siblings
        previousNodeInPath[connectedNode] = node;
      }
    }
  }

  // We iterated through all the nodes, and no paths lead to the ship
  return null;
}

function getShortestPathToShip(previousNodeInPath: PreviousNodeMap): string[] {
  const pathToShip = [];

  // We start at the final node and work our way backward to the start
  let node = END_NODE;

  while (node !== null) {
    pathToShip.push(node);

    // Doing a look up on the hash table for each node
    // will yield the previous node in the path
    node = previousNodeInPath[node];
  }

  // Since we worked our way backward,
  // we must reverse the path to be in the correct order base -> ship
  return pathToShip.reverse();
}

class Queue {
  queue: string[];
  head: number;

  constructor() {
    this.queue = [];
    this.head = 0;
  }
  // Append at the back and advance a head index without shifting the array
  enqueue(item: string) {
    this.queue.push(item);
  }
  dequeue(): string {
    return this.queue[this.head++];
  }
  size(): number {
    return this.queue.length - this.head;
  }
}

Practice this implementation

Open Pilot a Rocket to run the implementation against the course tests, then change one boundary condition and explain the first failing case. The editor supplies the starter signature and any node types or helper APIs used above. Copy the implementation into that environment; the snippet is the solution body, without the input parser or test driver. Your saved progress belongs to the original lesson.

For more TypeScript conventions and practice problems, use the TypeScript interview guide.

Try the exercise

Write your own implementation in the course editor. This walkthrough belongs to the same lesson; your course progress stays with that exercise. Exercise access follows the course’s access settings.