Path Compression in Union Find in DSA C# - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main purpose of path compression in Union Find?

Path compression helps speed up the 'find' operation by making nodes point directly to the root, flattening the structure for faster future queries.

beginner

In Union Find, what does the 'find' function return after path compression?

It returns the root or representative of the set, and updates all nodes along the path to point directly to this root.

intermediate

How does path compression affect the tree structure in Union Find?

It flattens the tree by making every node on the path from a node to the root point directly to the root, reducing tree height.

intermediate

Why is path compression important for the efficiency of Union Find?

Because it reduces the time complexity of future 'find' operations, making them almost constant time on average.

advanced

Show the effect of path compression on the parent array after calling find on a deep node.

After calling find on a deep node, all nodes on the path will have their parent updated to the root, making the parent array reflect a flat structure.

What does path compression do in the Union Find data structure?

A Deletes nodes from the set

B Merges two sets by size

C Makes every node point directly to the root after find

D Creates new sets for each element

Path compression updates nodes on the find path to point directly to the root, speeding up future finds.

Which operation benefits most from path compression?

A Find

B Delete

C Insert

D Union

The find operation becomes faster because path compression flattens the tree.

After path compression, the height of the tree is usually:

A Reduced

B Increased

C Unchanged

D Doubled

Path compression reduces the tree height by making nodes point directly to the root.

What is the time complexity of find with path compression over many operations?

A O(n)

B Amortized almost O(1)

C O(log n)

D O(n^2)

Path compression makes find operations almost constant time on average.

Which of these is NOT a benefit of path compression?

A Improved overall efficiency

B Flatter tree structure

C Faster find operations

D Increased memory usage

Path compression does not increase memory usage; it optimizes the structure.

Explain how path compression works in the Union Find data structure.

Think about what happens to nodes when you call find on a deep node.

Describe the impact of path compression on the time complexity of Union Find operations.

Consider how flattening the tree helps future operations.

Practice

1. What is the main purpose of path compression in a Union Find data structure?

easy

A. To speed up the find operation by flattening the tree

B. To merge two sets without checking their roots

C. To delete elements from the set efficiently

D. To sort the elements in each set

Solution

1. Step 1: Understand the role of path compression

   Path compression is used during the find operation to make future queries faster by making nodes point directly to the root.

2. Step 2: Identify the effect on the tree structure

   This flattens the tree, reducing the height and speeding up subsequent find calls.

3. Final Answer:

   To speed up the find operation by flattening the tree -> Option A

4. Quick Check:

   Path compression = flatten tree = faster find [OK]

Hint: Path compression flattens trees to speed up find [OK]

Common Mistakes:

• Thinking path compression merges sets
• Confusing path compression with union by rank
• Believing it deletes elements

2. Which of the following is the correct syntax for the find method with path compression in C#?

easy

A. int Find(int x) { while (parent[x] != x) x = parent[x]; return x; }

B. int Find(int x) { return parent[x]; }

C. int Find(int x) { if (parent[x] != x) parent[x] = Find(parent[x]); return parent[x]; }

D. int Find(int x) { if (parent[x] == x) return x; else return Find(x); }

Solution

1. Step 1: Check for path compression in the code

   int Find(int x) { if (parent[x] != x) parent[x] = Find(parent[x]); return parent[x]; } updates parent[x] to the root during recursion, which is path compression.

2. Step 2: Verify other options

   int Find(int x) { while (parent[x] != x) x = parent[x]; return x; } uses a loop but does not update parents. int Find(int x) { return parent[x]; } returns parent directly without recursion. int Find(int x) { if (parent[x] == x) return x; else return Find(x); } causes infinite recursion.

3. Final Answer:

   int Find(int x) { if (parent[x] != x) parent[x] = Find(parent[x]); return parent[x]; } -> Option C

4. Quick Check:

   Path compression updates parent during find [OK]

Hint: Look for recursive parent update in find method [OK]

Common Mistakes:

• Using loop without updating parents
• Returning parent without recursion
• Infinite recursion by calling Find(x) instead of Find(parent[x])

3. Given the following code snippet, what will be the output after calling uf.Find(3)?

var uf = new UnionFind(5);
uf.Union(1, 2);
uf.Union(2, 3);
Console.WriteLine(uf.Find(3));

Assume Union merges sets by attaching root of second to first and Find uses path compression.

medium

A. 2

B. 1

C. 3

D. 4

Solution

1. Step 1: Trace the unions

   Union(1,2) makes 1 the root of 2. Union(2,3) attaches 3 under 2, so root of 3 is 1 through 2.

2. Step 2: Find root of 3 with path compression

   Find(3) follows parent chain 3 -> 2 -> 1, returns 1 and compresses path so 3 points directly to 1.

3. Final Answer:

   1 -> Option B

4. Quick Check:

   Root after unions = 1 [OK]

Hint: Follow parent chain after unions to find root [OK]

Common Mistakes:

• Assuming root is 3 or 2 without tracing
• Ignoring path compression effect
• Confusing union direction

4. Identify the bug in this Find method implementation with path compression:

int Find(int x) {
  if (parent[x] == x) return x;
  else return Find(x);
}

medium

A. It should use a loop instead of recursion

B. It does not return the root correctly

C. It does not perform path compression

D. It causes infinite recursion because it calls Find(x) instead of Find(parent[x])

Solution

1. Step 1: Analyze the recursive call

   The method calls Find(x) again without changing x, causing infinite recursion.

2. Step 2: Correct recursive call for path compression

   It should call Find(parent[x]) to move up the tree and compress paths.

3. Final Answer:

   It causes infinite recursion because it calls Find(x) instead of Find(parent[x]) -> Option D

4. Quick Check:

   Recursive call must use parent[x] [OK]

Hint: Recursive find must call Find(parent[x]) not Find(x) [OK]

Common Mistakes:

• Calling Find(x) again causes infinite loop
• Forgetting to update parent for compression
• Using loop but missing path compression

5. You have a Union Find with 6 elements (0 to 5). After these operations:

uf.Union(0, 1);
uf.Union(1, 2);
uf.Union(3, 4);
uf.Union(4, 5);
uf.Find(2);
uf.Find(5);
uf.Union(2, 5);
uf.Find(5);

How many elements will directly point to the root of their set after all operations with path compression?

hard

A. 6

B. 4

C. 3

D. 2

Solution

1. Step 1: Track unions and finds

   Unions create two sets: {0,1,2} and {3,4,5}. Finds on 2 and 5 compress paths so 0 and 3 become roots with direct children.

2. Step 2: After union(2,5) and find(5), all nodes in one set with path compression

   After union(2,5), sets merge. Find(5) compresses path so nodes 2 and 5 point directly to root. Nodes 0 and 1 also point to root from earlier compression.

3. Step 3: Count elements directly pointing to root

   Elements 0,1,2,3,4,5 all point directly to the root after the final find(5) call due to path compression.

4. Final Answer:

   6 -> Option A

5. Quick Check:

   All nodes point directly to root after final find call [OK]

Hint: Count nodes updated by find calls for direct root pointers [OK]

Common Mistakes:

• Assuming all nodes point directly after union
• Ignoring path compression effect only on find calls
• Counting nodes without tracing parent updates