A bipartite graph is a graph whose nodes can be divided into two groups so that no edge connects nodes within the same group.
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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 check if the graph can be colored without conflicts.
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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 have the same color, breaking the bipartite rule.
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beginner
What data structure is typically used to store the graph for bipartite check?
An adjacency list is commonly used to store the graph because it efficiently represents edges for each node.
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intermediate
Why do we need to check all nodes in the graph when checking bipartiteness?
Because the graph may be disconnected, so we must check each connected part to ensure the whole graph is bipartite.
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What colors are used in bipartite graph check?
ATwo colors
BThree colors
COnly one color
DFour colors
✗ Incorrect
Bipartite graphs use two colors to separate nodes into two groups.
If a graph has an odd-length cycle, is it bipartite?
AYes
BNo
COnly if it has even nodes
DOnly if it is disconnected
✗ Incorrect
Graphs with odd-length cycles cannot be bipartite.
Which traversal can be used to check bipartiteness?
ABoth BFS and DFS
BDFS
CBFS
DNeither BFS nor DFS
✗ Incorrect
Both BFS and DFS can be used to color the graph and check bipartiteness.
What does a color value of -1 usually mean in bipartite check code?
ANode is visited twice
BNode is colored red
CNode is colored blue
DNode is uncolored
✗ Incorrect
A color of -1 means the node has not been colored yet.
Why do we assign opposite colors to neighbors in bipartite check?
ATo count edges
BTo make the graph connected
CTo ensure no two connected nodes share the same color
DTo find shortest path
✗ Incorrect
Assigning opposite colors ensures edges connect nodes of different colors.
Explain how to check if a graph is bipartite using BFS or DFS.
Think about coloring nodes and checking neighbors.
You got /5 concepts.
Describe why a graph with an odd cycle cannot be bipartite.
Consider coloring nodes around a cycle.
You got /4 concepts.
Practice
(1/5)
1. What does it mean for a graph to be bipartite?
easy
A. Its vertices can be divided into two sets with no edges inside the same set
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
Step 1: Understand bipartite graph definition
A bipartite graph is one where vertices can be split into two groups so that no edge connects vertices within the same group.
Step 2: Compare options with definition
Only Its vertices can be divided into two sets with no edges inside the same set matches this definition exactly. Other options describe unrelated properties.
Final Answer:
Its vertices can be divided into two sets with no edges inside the same set -> Option A
Quick Check:
Bipartite = Two sets, 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 Java code snippet correctly initializes a graph as an adjacency list for bipartite check?
easy
A. List graph = new ArrayList<>();
B. int graph = new int[5][5];
C. Map graph = new HashMap<>();
D. Set<Integer> graph = new HashSet<>();
Solution
Step 1: Identify adjacency list structure
An adjacency list for a graph is usually a list of lists, where each inner list holds neighbors of a vertex.
Step 2: Match code snippets to adjacency list
List<List<Integer>> graph = new ArrayList<>(); uses List of Lists, suitable for adjacency list. int graph = new int[5][5]; is a 2D array (adjacency matrix), not list. Options A and C use Set and Map, which are not standard adjacency lists.
Final Answer:
List<List<Integer>> graph = new ArrayList<>(); -> Option A
Quick Check:
Adjacency list = List of Lists [OK]
Hint: Adjacency list uses List of Lists in Java [OK]
Common Mistakes:
Using 2D arrays instead of lists
Using Map or Set incorrectly for adjacency
Not initializing the list properly
3. What is the output of the following Java code snippet checking bipartite for a graph with edges: 0-1, 1-2, 2-3, 3-0?
List<List<Integer>> graph = new ArrayList<>();
for (int i = 0; i < 4; i++) graph.add(new ArrayList<>());
graph.get(0).add(1); graph.get(1).add(0);
graph.get(1).add(2); graph.get(2).add(1);
graph.get(2).add(3); graph.get(3).add(2);
graph.get(3).add(0); graph.get(0).add(3);
boolean result = isBipartite(graph);
System.out.println(result);
The graph has edges forming a cycle of length 4: 0-1-2-3-0.
Step 2: Check bipartite condition for even cycle
Even length cycles (4) are bipartite, so the graph should be bipartite. But the edges connect 0-3 and 3-2, forming a cycle of length 4.
Step 3: Re-examine edges carefully
The cycle is 0-1-2-3-0, which is even length, so graph is bipartite. So output should be true.
Final Answer:
true -> Option B
Quick Check:
Even cycle graph is bipartite = true [OK]
Hint: Even length cycles are bipartite, odd length are not [OK]
Common Mistakes:
Thinking all cycles are not bipartite
Confusing cycle length parity
Assuming runtime errors without cause
4. Identify the bug in this Java method for bipartite check:
boolean isBipartite(List<List<Integer>> graph) {
int n = graph.size();
int[] colors = new int[n];
Arrays.fill(colors, -1);
for (int i = 0; i < n; i++) {
if (colors[i] == -1) {
if (!dfsCheck(graph, i, colors, 0)) return false;
}
}
return true;
}
boolean dfsCheck(List<List<Integer>> graph, int node, int[] colors, int color) {
colors[node] = color;
for (int neighbor : graph.get(node)) {
if (colors[neighbor] == -1) {
if (!dfsCheck(graph, neighbor, colors, 1 - color)) return false;
} else if (colors[neighbor] == color) {
return false;
}
}
return true;
}
medium
A. Missing check for null graph
B. Colors array not initialized properly
C. Incorrect color flip in recursive call
D. DFS color assignment logic is correct, no bug
Solution
Step 1: Review color initialization
Colors array is initialized with -1, meaning uncolored, which is correct.
Step 2: Check DFS color assignment and recursion
DFS assigns current node color, then recursively assigns opposite color (1 - color) to neighbors. If neighbor has same color, returns false.
Step 3: Confirm logic correctness
The logic correctly detects bipartite property using DFS and color flipping. No bug found.
Final Answer:
DFS color assignment logic is correct, no bug -> Option D
Quick Check:
DFS color flip and checks are correct [OK]
Hint: DFS flips color 0 and 1 to check bipartite [OK]
Common Mistakes:
Forgetting to flip color in recursion
Not initializing colors array
Returning true too early
5. Given a graph with vertices 0 to 5 and edges: 0-1, 1-2, 2-3, 3-4, 4-5, 5-0, and 1-4, is the graph bipartite? Explain why.
hard
A. Yes, because all vertices can be colored the same
B. No, because it contains an odd length cycle
C. Yes, because it contains only even length cycles
D. No, because it has isolated vertices
Solution
Step 1: Identify cycles in the graph
The graph edges form a 6-node cycle: 0-1-2-3-4-5-0 and an extra edge 1-4.
Step 2: Check for odd length cycles
There exists an odd length cycle: 1-4-5-0-1 (length 4 is even, but 1-4-5-0-1 is actually length 4, so check carefully). Actually, the cycle 1-4-5-0-1 is length 4 (even). But consider cycle 1-2-3-4-1: edges 1-2,2-3,3-4,4-1 is length 4 (even). However, the presence of edge 1-4 creates a triangle cycle 1-4-5-0-1? No, 1-4-5-0-1 is length 4. But check for odd cycles: 1-4-5-0-1 is length 4, 0-1-4 is length 3? No edge 0-4. But edge 1-4 exists, 4-5, 5-0, 0-1. So cycle 1-4-5-0-1 is length 4. No odd cycles. But check cycle 1-4-5-0-1 is length 4. So no odd cycles. So graph is bipartite.
Step 3: Determine bipartite property
Absence of odd length cycles means the graph is bipartite.
Final Answer:
Yes, because it contains only even length cycles -> Option C
Quick Check:
No odd cycles = bipartite [OK]
Hint: Odd cycles break bipartite property [OK]
Common Mistakes:
Falsely assuming extra edge creates odd cycle (e.g., nonexistent 1-5)
Miscalculating cycle lengths
Confusing isolated vertices with bipartite condition
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