Collision Handling Using Chaining in DSA Go - Time & Space Complexity

Time Complexity: Collision Handling Using Chaining

O(n)

Understanding Time Complexity

When we use chaining to handle collisions in a hash table, we want to know how fast operations like insert or search run as the table grows.

We ask: How does the time to find or add an item change when more items are stored?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

func (ht *HashTable) Search(key string) *Node {
  index := ht.hash(key)
  current := ht.buckets[index]
  for current != nil {
    if current.key == key {
      return current
    }
    current = current.next
  }
  return nil
}

This code searches for a key in a hash table using chaining, by traversing the linked list at the hashed bucket.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Traversing the linked list at the bucket to find the key.
• How many times: Up to the number of elements stored in that bucket's chain.

How Execution Grows With Input

As more items are added, chains may get longer, making searches slower.

Input Size (n)	Approx. Operations
10	About 1 to 2 steps per search
100	About 10 steps if chains grow
1000	About 100 steps if chains are long

Pattern observation: If the number of buckets stays fixed, operations grow roughly linearly with n because chains get longer.

Final Time Complexity

Time Complexity: O(n)

This means in the worst case, searching can take time proportional to the number of items stored, if many keys collide into the same bucket.

Common Mistake

[X] Wrong: "Hash table search is always O(1) no matter what."

[OK] Correct: If many keys collide, the linked list grows, making search slower and closer to O(n).

Interview Connect

Understanding how chaining affects time helps you explain hash table behavior clearly and shows you know real-world trade-offs.

Self-Check

"What if we resize the hash table and rehash keys when load grows? How would the time complexity change?"

Practice

1. What is the main idea behind collision handling using chaining in hash tables?

easy

A. Use open addressing to find another empty slot

B. Resize the hash table to avoid collisions

C. Store multiple elements in a linked list at the same index when collisions occur

D. Ignore collisions and overwrite existing data

Solution

1. Step 1: Understand collision in hash tables

   When two keys hash to the same index, a collision happens.

2. Step 2: How chaining handles collisions

   Chaining stores all collided elements in a linked list at that index.

3. Final Answer:

   Store multiple elements in a linked list at the same index when collisions occur -> Option C

4. Quick Check:

   Chaining = linked list at index [OK]

Hint: Chaining means linked lists at each index [OK]

Common Mistakes:

• Thinking chaining resizes the table
• Confusing chaining with open addressing
• Assuming collisions are ignored

2. Which of the following is the correct way to declare a hash table with chaining in Go using slices of linked lists?

easy

A. var table [10]*Node

B. var table = make([]*Node, 10)

C. var table = make(map[int]*Node)

D. var table = [10]Node{}

Solution

1. Step 1: Understand Go slice declaration for chaining

   Chaining uses a slice of pointers to linked list nodes for dynamic size.

2. Step 2: Identify correct syntax

   Using make([]*Node, 10) creates a slice of 10 pointers to Node, suitable for chaining.

3. Final Answer:

   var table = make([]*Node, 10) -> Option B

4. Quick Check:

   Slice of pointers = make([]*Node, size) [OK]

Hint: Use make([]*Node, size) for chaining table [OK]

Common Mistakes:

• Using arrays instead of slices limits flexibility
• Using map instead of slice for chaining
• Declaring slice without make causes nil slice

3. Consider the following Go code snippet for inserting keys into a hash table with chaining. What will be the output after inserting keys 5 and 15 if the hash function is key % 10?

type Node struct {
    key  int
    next *Node
}

func insert(table []*Node, key int) {
    index := key % 10
    newNode := &Node{key: key}
    newNode.next = table[index]
    table[index] = newNode
}

func printTable(table []*Node) {
    for i, node := range table {
        print(i, ": ")
        for n := node; n != nil; n = n.next {
            print(n.key, " -> ")
        }
        println("nil")
    }
}

func main() {
    table := make([]*Node, 10)
    insert(table, 5)
    insert(table, 15)
    printTable(table)
}

medium

A. 15 -> 5 -> nil at index 5

B. 15 -> nil at index 5 and 5 -> nil at index 5

C. 5 -> nil at index 5 and 15 -> nil at index 5

D. 5 -> 15 -> nil at index 5

Solution

1. Step 1: Calculate hash index for keys 5 and 15

   Both 5 % 10 and 15 % 10 equal 5, so both keys go to index 5.

2. Step 2: Trace insertion order in chaining

   First insert 5 at index 5, then insert 15 which becomes new head pointing to 5.

3. Final Answer:

   15 -> 5 -> nil at index 5 -> Option A

4. Quick Check:

   New nodes added at head = 15 first [OK]

Hint: New nodes go to head of list in chaining [OK]

Common Mistakes:

• Assuming insertion appends at tail
• Mixing up hash index calculation
• Printing nodes in wrong order

4. The following Go code tries to insert keys into a hash table with chaining but causes a runtime panic. What is the error?

type Node struct {
    key  int
    next *Node
}

func insert(table []*Node, key int) {
    index := key % len(table)
    if table[index] == nil {
        table[index].key = key
    } else {
        newNode := &Node{key: key, next: table[index]}
        table[index] = newNode
    }
}

func main() {
    table := make([]*Node, 10)
    insert(table, 7)
}

medium

A. Nil pointer dereference when assigning to table[index].key

B. Index out of range error due to wrong hash calculation

C. Infinite loop in insert function

D. Compilation error due to missing return statement

Solution

1. Step 1: Analyze the nil check and assignment

   If table[index] is nil, trying to assign table[index].key causes nil pointer dereference.

2. Step 2: Understand pointer initialization requirement

   Must create a new Node and assign pointer to table[index] before setting key.

3. Final Answer:

   Nil pointer dereference when assigning to table[index].key -> Option A

4. Quick Check:

   Assigning field on nil pointer causes panic [OK]

Hint: Initialize pointer before assigning fields [OK]

Common Mistakes:

• Ignoring nil pointer before field assignment
• Assuming slice elements auto-initialize
• Confusing compile error with runtime panic

5. You want to implement a hash table with chaining in Go that supports deletion of keys. Which approach correctly removes a key from the chain at the hashed index?

hard

A. Replace the key with zero but keep the node in the list

B. Set the entire linked list at the index to nil to remove the key

C. Resize the hash table and rehash all keys except the one to delete

D. Traverse the linked list at the index, keep track of previous node, and adjust pointers to skip the node with the key

Solution

1. Step 1: Understand deletion in chaining

   To delete a key, find it in the linked list and remove its node by adjusting pointers.

2. Step 2: Why other options fail

   Setting entire list to nil removes all keys, replacing key with zero keeps node, resizing is inefficient.

3. Final Answer:

   Traverse the linked list at the index, keep track of previous node, and adjust pointers to skip the node with the key -> Option D

4. Quick Check:

   Proper deletion adjusts pointers in linked list [OK]

Hint: Delete by pointer adjustment in linked list [OK]

Common Mistakes:

• Removing entire chain instead of one key
• Leaving empty nodes with zero keys
• Rehashing unnecessarily on deletion