Adjacency List Representation in DSA Typescript - Time & Space Complexity

Time Complexity: Adjacency List Representation

O(n + e)

Understanding Time Complexity

We want to understand how fast we can access and traverse a graph stored as an adjacency list.

How does the time to visit nodes and edges grow as the graph gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

// Traverse all nodes and their neighbors in an adjacency list
function traverseGraph(adjList: Map<number, number[]>) {
  for (const node of adjList.keys()) {
    const neighbors = adjList.get(node) || [];
    for (const neighbor of neighbors) {
      // process edge from node to neighbor
    }
  }
}
    

This code visits every node and then visits each neighbor connected to that node.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The nested loops: outer loop over all nodes, inner loop over each node's neighbors.
• How many times: Outer loop runs once per node (n times), inner loop runs once per edge connected to that node.

How Execution Grows With Input

As the graph grows, the number of nodes (n) and edges (e) increase.

Input Size (n nodes, e edges)	Approx. Operations
10 nodes, 15 edges	About 10 (nodes) + 15 (edges) = 25 operations
100 nodes, 200 edges	About 100 + 200 = 300 operations
1000 nodes, 5000 edges	About 1000 + 5000 = 6000 operations

Pattern observation: The total work grows roughly with the sum of nodes and edges.

Final Time Complexity

Time Complexity: O(n + e)

This means the time to traverse depends on how many nodes and edges the graph has combined.

Common Mistake

[X] Wrong: "Traversal time is just O(n) because we visit each node once."

[OK] Correct: We also visit all edges connected to nodes, so edges add to the total work and cannot be ignored.

Interview Connect

Understanding adjacency list traversal time helps you explain graph algorithms clearly and shows you know how data size affects performance.

Self-Check

"What if the graph was stored as an adjacency matrix instead? How would the time complexity change?"

Practice

1. What does an adjacency list represent in graph data structures?

easy

A. A list of all nodes without connections

B. A matrix showing distances between nodes

C. A queue of nodes to visit next

D. A list where each node stores its connected neighbors

Solution

1. Step 1: Understand adjacency list concept

   An adjacency list stores each node with a list of its neighbors, showing direct connections.

2. Step 2: Compare options with definition

   Only A list where each node stores its connected neighbors correctly describes this structure; others describe different concepts.

3. Final Answer:

   A list where each node stores its connected neighbors -> Option D

4. Quick Check:

   Adjacency list = neighbors list [OK]

Hint: Adjacency list always stores neighbors per node [OK]

Common Mistakes:

• Confusing adjacency list with adjacency matrix
• Thinking it stores distances instead of neighbors
• Assuming it is a queue or unrelated structure

2. Which of the following is the correct TypeScript syntax to declare an adjacency list for a graph with nodes as numbers?

easy

A. const graph: number[][] = [];

B. const graph: Map = new Map();

C. const graph: Record = {};

D. const graph: Array<number> = [];

Solution

1. Step 1: Identify adjacency list type

   An adjacency list maps each node (number) to an array of connected nodes (number[]).

2. Step 2: Match TypeScript syntax

   Map correctly represents this; others are incorrect types or structures.

3. Final Answer:

   const graph: Map = new Map(); -> Option B

4. Quick Check:

   Map = adjacency list [OK]

Hint: Use Map with number keys and array values for adjacency list [OK]

Common Mistakes:

• Using Record which maps to single number, not array
• Using number[][] without keys for nodes
• Using Array<number> which is just a list, not adjacency

3. Given the following TypeScript code, what is the output after adding edges?

const graph: Map = new Map();
graph.set(1, [2, 3]);
graph.set(2, [1]);
graph.set(3, [1, 4]);
graph.set(4, [3]);
console.log(graph.get(3));

medium

A. [2, 3]

B. [3, 4]

C. [1, 4]

D. undefined

Solution

1. Step 1: Trace graph.set calls

   Node 3 is set with neighbors [1, 4].

2. Step 2: Check graph.get(3)

   Returns the array [1, 4] assigned to node 3.

3. Final Answer:

   [1, 4] -> Option C

4. Quick Check:

   graph.get(3) = [1, 4] [OK]

Hint: graph.get(node) returns neighbors array [OK]

Common Mistakes:

• Confusing neighbors of node 3 with node 1 or 2
• Expecting undefined if not careful with set calls
• Mixing up array contents order

4. Identify the error in this TypeScript adjacency list code snippet:

const graph: Map = new Map();
graph.set(1, [2]);
graph.set(2, [1]);
graph.get(3).push(1);

medium

A. graph.get(3) returns undefined, so push causes error

B. Map keys must be strings, not numbers

C. graph.set should use arrays of strings, not numbers

D. Missing initialization of graph variable

Solution

1. Step 1: Check graph.get(3) call

   Node 3 was never set, so graph.get(3) returns undefined.

2. Step 2: Understand push on undefined

   Calling push on undefined causes runtime error.

3. Final Answer:

   graph.get(3) returns undefined, so push causes error -> Option A

4. Quick Check:

   Accessing unset key returns undefined [OK]

Hint: Check if key exists before pushing to adjacency list [OK]

Common Mistakes:

• Assuming graph.get(3) returns empty array automatically
• Thinking Map keys must be strings (numbers are allowed)
• Ignoring runtime error from push on undefined

5. You want to represent a directed graph with nodes 1 to 4 using an adjacency list in TypeScript. Which code correctly adds an edge from node 2 to node 4 without affecting other edges?

const graph: Map = new Map();
graph.set(1, [2]);
graph.set(2, [3]);
graph.set(3, []);
graph.set(4, []);
// Add edge from 2 to 4 here

hard

A. graph.get(2)?.push(4);

B. graph.set(2, [4]);

C. graph.set(4, [2]);

D. graph.get(4)?.push(2);

Solution

1. Step 1: Understand existing edges

   Node 2 currently has neighbors [3]. We want to add 4 without removing 3.

2. Step 2: Choose correct method to add edge

   Using graph.get(2)?.push(4) adds 4 to existing array, preserving [3]. graph.set(2, [4]) replaces neighbors, removing 3.

3. Final Answer:

   graph.get(2)?.push(4); -> Option A

4. Quick Check:

   Use push to add edge without overwriting [OK]

Hint: Use push on existing neighbors to add edges safely [OK]

Common Mistakes:

• Overwriting neighbors array with set instead of pushing
• Adding edge to wrong node
• Confusing direction of edge in directed graph