Adjacency List Representation in DSA Javascript - Time & Space Complexity

Time Complexity: Adjacency List Representation

O(k)

Understanding Time Complexity

We want to understand how fast we can access and explore connections in a graph using adjacency lists.

How does the time to check neighbors grow as the graph gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

// Graph represented as adjacency list
const graph = {
  0: [1, 2],
  1: [0, 3],
  2: [0],
  3: [1]
};

// Function to print neighbors of a node
function printNeighbors(node) {
  for (const neighbor of graph[node]) {
    console.log(neighbor);
  }
}
    

This code stores graph connections in lists and prints all neighbors of a given node.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Looping through the neighbors list of a node.
• How many times: Equal to the number of neighbors that node has.

How Execution Grows With Input

As the graph grows, the time to print neighbors depends on how many neighbors the node has.

Input Size (n = total nodes)	Approx. Operations (neighbors of node)
10	Depends on node degree, e.g., 2 neighbors
100	Depends on node degree, e.g., 5 neighbors
1000	Depends on node degree, e.g., 10 neighbors

Pattern observation: Time grows with the number of neighbors, not total nodes.

Final Time Complexity

Time Complexity: O(k) where k is the number of neighbors of the node.

This means the time depends only on how many connections the node has, not the whole graph size.

Common Mistake

[X] Wrong: "Accessing neighbors always takes O(n) time where n is total nodes."

[OK] Correct: We only loop through the node's neighbors, which is usually much less than total nodes.

Interview Connect

Knowing adjacency list time helps you explain graph traversal speed clearly and confidently in interviews.

Self-Check

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

Practice

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

easy

A. A list where each node stores its neighbors

B. A matrix showing connections between nodes

C. A list of all nodes without connections

D. A list of edges sorted by weight

Solution

1. Step 1: Understand adjacency list concept

   An adjacency list stores each node with a list of its neighbors or connected nodes.

2. Step 2: Compare with other graph representations

   An adjacency matrix is a 2D array, not a list of neighbors. Other options describe different structures.

3. Final Answer:

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

4. Quick Check:

   Adjacency list = neighbors list [OK]

Hint: Adjacency list always stores neighbors for each node [OK]

Common Mistakes:

• Confusing adjacency list with adjacency matrix
• Thinking it stores edges sorted by weight
• Assuming it lists nodes without connections only

2. Which of the following is the correct JavaScript syntax to initialize an empty adjacency list for a graph?

easy

A. const graph = [];

B. const graph = new Map();

C. const graph = {};

D. const graph = new Set();

Solution

1. Step 1: Identify suitable data structure for adjacency list

   An adjacency list can be implemented using a Map to store nodes and their neighbors efficiently.

2. Step 2: Check syntax correctness

   new Map() creates an empty map. Arrays or objects can be used but Map is preferred for graph keys. Set is for unique values, not key-value pairs.

3. Final Answer:

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

4. Quick Check:

   Use Map() for adjacency list initialization [OK]

Hint: Use Map() to store nodes and neighbors in adjacency list [OK]

Common Mistakes:

• Using Set which does not store key-value pairs
• Using empty array which is less clear for key-value
• Using empty object but Map is better for keys

3. Given the following adjacency list representation in JavaScript, what will be the output of console.log(graph.get('A'));?

const graph = new Map();
graph.set('A', ['B', 'C']);
graph.set('B', ['A', 'D']);
graph.set('C', ['A']);
graph.set('D', ['B']);

medium

A. ['B', 'D']

B. ['A', 'D']

C. ['C', 'D']

D. ['B', 'C']

Solution

1. Step 1: Locate the key 'A' in the adjacency list

   The graph Map has key 'A' with value ['B', 'C'] representing neighbors.

2. Step 2: Understand what graph.get('A') returns

   It returns the array of neighbors for 'A', which is ['B', 'C'].

3. Final Answer:

   ['B', 'C'] -> Option D

4. Quick Check:

   graph.get('A') = ['B', 'C'] [OK]

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

Common Mistakes:

• Confusing neighbors of 'A' with neighbors of 'B'
• Expecting a string instead of array
• Mixing up keys and values in Map

4. The following code attempts to add an edge from node 'A' to node 'D' in an adjacency list but has a bug. What is the error?

const graph = new Map();
graph.set('A', ['B', 'C']);
// Add edge from A to D
graph.get('A').push('D');
console.log(graph.get('A'));

medium

A. graph.get('A') returns undefined causing error

B. Cannot push to array returned by graph.get('A')

C. The code works correctly and adds 'D' to neighbors

D. graph.set should be used instead of push

Solution

1. Step 1: Check if graph.get('A') returns an array

   graph.get('A') returns ['B', 'C'], an array, so push is valid.

2. Step 2: Verify if push adds 'D' correctly

   push('D') adds 'D' to the array, so neighbors become ['B', 'C', 'D'].

3. Final Answer:

   The code works correctly and adds 'D' to neighbors -> Option C

4. Quick Check:

   push on neighbors array works [OK]

Hint: graph.get(node) returns array; push adds neighbor [OK]

Common Mistakes:

• Assuming graph.get returns undefined if key exists
• Thinking push cannot modify array in Map
• Confusing push with set method

5. You want to represent a directed graph with nodes 'X', 'Y', 'Z' where edges are X->Y, Y->Z, and Z->X. Which adjacency list correctly represents this graph in JavaScript?

hard

A. const graph = new Map([['X', ['Y']], ['Y', ['Z']], ['Z', ['X']]]);

B. const graph = new Map([['X', ['Y', 'Z']], ['Y', ['X']], ['Z', ['Y']]]);

C. const graph = new Map([['X', ['Z']], ['Y', ['X']], ['Z', ['Y']]]);

D. const graph = new Map([['X', ['Y']], ['Y', ['X', 'Z']], ['Z', []]]);

Solution

1. Step 1: Understand directed edges

   Edges are X->Y, Y->Z, Z->X, so each node points only to its direct neighbors.

2. Step 2: Match edges to adjacency list entries

   'X' neighbors: ['Y'], 'Y' neighbors: ['Z'], 'Z' neighbors: ['X'] matches const graph = new Map([['X', ['Y']], ['Y', ['Z']], ['Z', ['X']]]); exactly.

3. Final Answer:

   const graph = new Map([['X', ['Y']], ['Y', ['Z']], ['Z', ['X']]]); -> Option A

4. Quick Check:

   Directed edges match adjacency list neighbors [OK]

Hint: Each node's list shows only nodes it points to [OK]

Common Mistakes:

• Including neighbors that don't have edges from the node
• Mixing up direction of edges
• Adding extra neighbors not in edges