Linear Search Algorithm in DSA C - Time & Space Complexity

Time Complexity: Linear Search Algorithm

O(n)

Understanding Time Complexity

We want to understand how the time taken by linear search changes as the list size grows.

How does the number of steps grow when we look for an item in a list?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

int linearSearch(int arr[], int n, int target) {
    for (int i = 0; i < n; i++) {
        if (arr[i] == target) {
            return i;
        }
    }
    return -1;
}
    

This code looks for a target value in an array by checking each element one by one.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Checking each element in the array to see if it matches the target.
• How many times: Up to n times, where n is the size of the array.

How Execution Grows With Input

As the list gets bigger, the number of checks grows roughly the same as the list size.

Input Size (n)	Approx. Operations
10	Up to 10 checks
100	Up to 100 checks
1000	Up to 1000 checks

Pattern observation: The number of steps grows directly with the size of the list.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the item grows in a straight line with the list size.

Common Mistake

[X] Wrong: "Linear search always takes the same time no matter the list size."

[OK] Correct: The search time depends on where the target is or if it is missing, so bigger lists usually take more time.

Interview Connect

Understanding linear search time helps you compare it with faster methods and shows you how to analyze simple algorithms clearly.

Self-Check

"What if the array was sorted and we used binary search instead? How would the time complexity change?"

Practice

1. What is the main idea behind the Linear Search Algorithm?

easy

A. Check each element one by one until the target is found or list ends

B. Divide the list into halves repeatedly to find the target

C. Sort the list first then search using binary method

D. Use a hash table to find the target instantly

Solution

1. Step 1: Understand linear search process

   Linear search checks each element in order from start to end.

2. Step 2: Compare with other search methods

   Other methods like binary search divide the list, but linear search does not.

3. Final Answer:

   Check each element one by one until the target is found or list ends -> Option A

4. Quick Check:

   Linear search = check elements one by one [OK]

Hint: Linear search checks elements one by one [OK]

Common Mistakes:

• Confusing linear search with binary search
• Thinking linear search requires sorted list
• Assuming instant search with hash tables

2. Which of the following is the correct syntax to start a linear search loop in C for an array arr of size n?

easy

A. for (int i = 0; i < n; i++)

B. for (int i = 0; i <= n; i++)

C. for (int i = 1; i < n; i++)

D. for (int i = 1; i <= n; i++)

Solution

1. Step 1: Understand array indexing in C

   Arrays in C start at index 0 and go up to n-1 for size n.

2. Step 2: Choose correct loop condition

   The loop should run from 0 to less than n, so i < n is correct.

3. Final Answer:

   for (int i = 0; i < n; i++) -> Option A

4. Quick Check:

   Loop from 0 to n-1 = for(i=0; i<n; i++) [OK]

Hint: Array index starts at 0, loop till i < n [OK]

Common Mistakes:

• Using <= n causes out-of-bounds access
• Starting loop at 1 misses first element
• Confusing array size with last index

3. What will be the output of the following C code?

int arr[] = {4, 2, 7, 1, 9};
int n = 5;
int target = 7;
int index = -1;
for (int i = 0; i < n; i++) {
  if (arr[i] == target) {
    index = i;
    break;
  }
}
printf("%d", index);

medium

A. 3

B. 2

C. -1

D. 7

Solution

1. Step 1: Trace the loop to find target 7

   Check elements: arr[0]=4 (no), arr[1]=2 (no), arr[2]=7 (yes), stop loop.

2. Step 2: Identify index where target found

   Target 7 found at index 2, so index = 2.

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Target 7 at arr[2] = 2 [OK]

Hint: Stop loop when target found, print index [OK]

Common Mistakes:

• Printing value instead of index
• Not breaking loop and printing last index
• Confusing index with element value

4. Find the error in this linear search code snippet in C:

int linearSearch(int arr[], int n, int target) {
  for (int i = 1; i <= n; i++) {
    if (arr[i] == target) {
      return i;
    }
  }
  return -1;
}

medium

A. The array parameter should be a pointer, not an array

B. The function should return the element, not the index

C. The return -1 should be inside the loop

D. Loop starts at 1 and goes to <= n, causing out-of-bounds access

Solution

1. Step 1: Check loop indexing for array access

   Array indices in C start at 0 and go to n-1, but loop starts at 1 and goes to n, causing out-of-bounds at arr[n].

2. Step 2: Identify correct loop bounds

   Loop should start at 0 and run while i < n to avoid invalid access.

3. Final Answer:

   Loop starts at 1 and goes to <= n, causing out-of-bounds access -> Option D

4. Quick Check:

   Array index out-of-bounds due to wrong loop limits [OK]

Hint: Array index starts at 0, loop i < n [OK]

Common Mistakes:

• Starting loop at 1 instead of 0
• Using <= n instead of < n in loop condition
• Returning element instead of index

5. You have an unsorted array arr with 10 elements where some elements repeat. You want to find the first occurrence index of the number 5 using linear search. Which approach is best to handle duplicates and return the correct index?

hard

A. Sort the array first, then use binary search to find 5

B. Traverse entire array, count all 5s, then return last index of 5

C. Traverse from start to end, return index immediately when 5 is found

D. Use a hash map to store counts, then find index of 5

Solution

1. Step 1: Understand requirement for first occurrence

   We want the first index where 5 appears, so searching from start is needed.

2. Step 2: Choose approach that stops at first match

   Linear search that returns immediately on first 5 found gives correct first occurrence index.

3. Final Answer:

   Traverse from start to end, return index immediately when 5 is found -> Option C

4. Quick Check:

   Stop at first match to get first occurrence [OK]

Hint: Return index immediately on first match [OK]

Common Mistakes:

• Counting all occurrences then returning last index
• Sorting changes original order, losing first occurrence
• Using hash map adds unnecessary complexity