Bipartite Graph Check in DSA Typescript - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a bipartite graph?

A bipartite graph is a graph whose nodes can be divided into two groups so that no edge connects nodes within the same group.

beginner

Which method is commonly used to check if a graph is bipartite?

We use graph coloring with two colors or Breadth-First Search (BFS) or Depth-First Search (DFS) to assign colors and check for conflicts.

beginner

In bipartite graph check, what does it mean if a node's neighbor has the same color?

It means the graph is not bipartite because two connected nodes share the same group, which is not allowed.

beginner

What data structure is useful to keep track of node colors during bipartite check?

An array or map to store colors for each node, typically using two values like 0 and 1 or -1 for uncolored.

intermediate

Why do we need to check all nodes in the graph when checking bipartiteness?

Because the graph might be disconnected, so we must check each connected component separately.

What is the main property of a bipartite graph?

A Nodes can be split into two groups with no edges inside the same group

B Every node connects to every other node

C Graph has no edges

D Graph contains cycles only

A bipartite graph's nodes can be divided into two groups with edges only between groups.

Which algorithm is commonly used to color nodes for bipartite check?

A Floyd-Warshall algorithm

B Dijkstra's algorithm

C Prim's algorithm

D Breadth-First Search (BFS)

BFS helps assign colors level by level to check bipartiteness.

If a neighbor node has the same color during bipartite check, what does it mean?

A Graph is bipartite

B Graph is not bipartite

C Graph is disconnected

D Graph is complete

Same color neighbors mean the graph is not bipartite.

What color value is usually used to mark uncolored nodes?

A -1

B 1

C 0

D 2

Uncolored nodes are often marked with -1 to distinguish from colored nodes.

Why must we check all nodes in the graph for bipartite property?

A Because nodes have weights

B Because all nodes have edges

C Because graph might be disconnected

D Because graph is always connected

Disconnected graphs have multiple components that must be checked separately.

Explain how to check if a graph is bipartite using BFS.

Think about coloring nodes level by level and checking conflicts.

Describe why a graph with an odd-length cycle cannot be bipartite.

Consider coloring nodes around a cycle and what happens at the end.

Practice

1. What does it mean if a graph is bipartite?

easy

A. Its vertices can be divided into two groups with no edges inside the same group

B. It has an equal number of vertices and edges

C. It contains at least one cycle

D. All vertices have the same degree

Solution

1. Step 1: Understand bipartite graph definition

   A bipartite graph can be split into two sets where no edges connect vertices within the same set.

2. Step 2: Compare options with definition

   Only Its vertices can be divided into two groups with no edges inside the same group matches this definition exactly.

3. Final Answer:

   Its vertices can be divided into two groups with no edges inside the same group -> Option A

4. Quick Check:

   Bipartite = Two groups, no internal edges [OK]

Hint: Bipartite means two groups with no edges inside groups [OK]

Common Mistakes:

• Confusing bipartite with equal vertices and edges
• Thinking bipartite means no cycles
• Assuming all vertices have same degree

2. Which TypeScript data structure is best to represent a graph for bipartite check?

easy

A. Adjacency list using Map

B. Array of numbers

C. String array

D. Single number variable

Solution

1. Step 1: Identify graph representation needs

   We need to store edges for each vertex efficiently to check bipartite property.

2. Step 2: Choose suitable data structure

   An adjacency list using Map stores neighbors for each vertex clearly and is efficient.

3. Final Answer:

   Adjacency list using Map<number, number[]> -> Option A

4. Quick Check:

   Graph as adjacency list = Map [OK]

Hint: Use adjacency list (Map) for graph edges [OK]

Common Mistakes:

• Using simple arrays without edge info
• Using strings which don't represent graph
• Using single variable instead of structure

3. What is the output of this TypeScript code that checks if a graph is bipartite?

const graph = new Map([
  [0, [1, 3]],
  [1, [0, 2]],
  [2, [1, 3]],
  [3, [0, 2]]
]);

function isBipartite(graph: Map): boolean {
  const color = new Map();
  for (const node of graph.keys()) {
    if (!color.has(node)) {
      const queue = [node];
      color.set(node, 0);
      while (queue.length) {
        const u = queue.shift()!;
        for (const v of graph.get(u)!) {
          if (!color.has(v)) {
            color.set(v, 1 - color.get(u)!);
            queue.push(v);
          } else if (color.get(v) === color.get(u)) {
            return false;
          }
        }
      }
    }
  }
  return true;
}

console.log(isBipartite(graph));

medium

A. false

B. true

C. undefined

D. SyntaxError

Solution

1. Step 1: Analyze graph structure

   The graph is a square cycle: 0-1-2-3-0, which is an even cycle and bipartite.

2. Step 2: Trace BFS coloring

   Starting from node 0 with color 0, neighbors get color 1, their neighbors color 0, no conflicts found.

3. Final Answer:

   true -> Option B

4. Quick Check:

   Even cycle graph is bipartite = true [OK]

Hint: Even cycles are bipartite, odd cycles are not [OK]

Common Mistakes:

• Assuming all cycles are not bipartite
• Confusing color assignment logic
• Missing BFS queue processing

4. Find the bug in this TypeScript function that checks if a graph is bipartite:

function isBipartite(graph: Map): boolean {
  const color = new Map();
  for (const node of graph.keys()) {
    if (!color.has(node)) {
      const queue = [node];
      color.set(node, 0);
      while (queue.length) {
        const u = queue.shift()!;
        for (const v of graph.get(u)!) {
          if (!color.has(v)) {
            color.set(v, color.get(u)!);
            queue.push(v);
          } else if (color.get(v) === color.get(u)) {
            return false;
          }
        }
      }
    }
  }
  return true;
}

medium

A. Missing return type boolean

B. queue.shift()! should be queue.pop()

C. color.set(v, color.get(u)!) should be color.set(v, 1 - color.get(u)!)

D. graph.get(u)! should be graph.get(v)!

Solution

1. Step 1: Identify color assignment error

   The code assigns the same color to neighbors, which breaks bipartite logic.

2. Step 2: Correct color assignment

   Neighbors must get opposite color: 1 - color of current node.

3. Final Answer:

   color.set(v, 1 - color.get(u)!) -> Option C

4. Quick Check:

   Neighbor color = opposite of current [OK]

Hint: Neighbors must have opposite colors [OK]

Common Mistakes:

• Assigning same color to neighbors
• Using pop instead of shift in BFS
• Incorrect graph access

5. Given a graph represented as adjacency list:

const graph = new Map([
  [0, [1, 2]],
  [1, [0, 3]],
  [2, [0, 3]],
  [3, [1, 2, 4]],
  [4, [3]]
]);

Is this graph bipartite? Choose the correct reasoning.

hard

A. Yes, because it has no odd-length cycles

B. No, because node 3 connects to nodes in the same set

C. Yes, because all nodes have even degree

D. No, because it contains a triangle (3-cycle)

Solution

1. Step 1: Identify cycles in the graph

   There is a triangle cycle: nodes 1-3-2-1 (edges 1-3, 3-2, 2-1), which is an odd-length cycle.

2. Step 2: Recall bipartite property about cycles

   Graphs containing odd-length cycles are not bipartite.

3. Final Answer:

   No, because it contains a triangle (3-cycle) -> Option D

4. Quick Check:

   Odd cycle present = not bipartite [OK]

Hint: Odd cycles mean graph is not bipartite [OK]

Common Mistakes:

• Falsely identifying triangle in 1-2-3 (actually 1-3-2 forms triangle)
• Assuming even degree means bipartite
• Confusing connectivity with bipartite property