Recursion on Arrays and Strings in DSA Python - Time & Space Complexity

Time Complexity: Recursion on Arrays and Strings

O(n)

Understanding Time Complexity

When we use recursion on arrays or strings, we call the same function repeatedly on smaller parts.

We want to know how the number of these calls grows as the input gets bigger.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

def sum_array(arr, n):
    if n == 0:
        return 0
    return arr[n-1] + sum_array(arr, n-1)

This function adds all elements of an array by calling itself on smaller parts until it reaches the start.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive call reducing the problem size by 1 each time.
• How many times: The function calls itself once for each element, so n times.

How Execution Grows With Input

Each new element adds one more recursive call, so the total calls grow directly with input size.

Input Size (n)	Approx. Operations
10	10 calls
100	100 calls
1000	1000 calls

Pattern observation: The number of calls grows linearly as input size increases.

Final Time Complexity

Time Complexity: O(n)

This means the time taken grows in direct proportion to the size of the array or string.

Common Mistake

[X] Wrong: "Recursion always makes the code slower exponentially."

[OK] Correct: Here, recursion calls happen once per element, so it grows linearly, not exponentially.

Interview Connect

Understanding how recursion scales helps you explain your solutions clearly and choose the best approach during interviews.

Self-Check

"What if the recursion called itself twice for each element (like in some tree problems)? How would the time complexity change?"

Practice

1. What does a recursive function do when processing an array or string?

easy

A. It loops through the array or string without calling itself.

B. It creates a new array or string without using recursion.

C. It calls itself with a smaller part of the array or string until a base case is reached.

D. It only processes the first element and stops.

Solution

1. Step 1: Understand recursion basics

   A recursive function calls itself with a smaller input to solve a problem step-by-step.

2. Step 2: Apply to arrays or strings

   For arrays or strings, recursion processes smaller parts until it reaches a base case (like empty array or string).

3. Final Answer:

   It calls itself with a smaller part of the array or string until a base case is reached. -> Option C

4. Quick Check:

   Recursion = smaller input calls [OK]

Hint: Recursion breaks problem into smaller parts [OK]

Common Mistakes:

• Thinking recursion processes entire array at once
• Confusing recursion with loops
• Ignoring the base case

2. Which of the following is the correct base case for a recursive function that reverses a string s?

easy

A. if s == s[::-1]: return s

B. if s == None: return s

C. if len(s) > 0: return s

D. if len(s) == 0: return s

Solution

1. Step 1: Identify base case for recursion

   The base case stops recursion. For strings, empty string means no more characters to reverse.

2. Step 2: Check options

   if len(s) == 0: return s checks if string length is zero and returns it, which is correct base case.

3. Final Answer:

   if len(s) == 0: return s -> Option D

4. Quick Check:

   Base case = empty string check [OK]

Hint: Base case usually checks for empty input [OK]

Common Mistakes:

• Using wrong condition for base case
• Checking reversed string equality as base case
• Returning input without base case

3. What is the output of this Python code?

def sum_array(arr):
    if len(arr) == 0:
        return 0
    return arr[0] + sum_array(arr[1:])

print(sum_array([1, 2, 3, 4]))

medium

A. 1234

B. 10

C. 24

D. Error

Solution

1. Step 1: Understand recursion on array sum

   Function adds first element to sum of rest of array recursively until empty array returns 0.

2. Step 2: Calculate sum step-by-step

   sum_array([1,2,3,4]) = 1 + sum_array([2,3,4]) = 1 + 2 + sum_array([3,4]) = 1 + 2 + 3 + sum_array([4]) = 1 + 2 + 3 + 4 + sum_array([]) = 1+2+3+4+0 = 10

3. Final Answer:

   10 -> Option B

4. Quick Check:

   Sum of [1,2,3,4] = 10 [OK]

Hint: Add first element + recursive sum of rest [OK]

Common Mistakes:

• Concatenating numbers instead of adding
• Forgetting base case returns 0
• Misunderstanding slicing arr[1:]

4. Find the error in this recursive function that checks if a string is a palindrome:

def is_palindrome(s):
    if len(s) <= 1:
        return True
    if s[0] != s[-1]:
        return False
    return is_palindrome(s[1:-1])

print(is_palindrome('racecar'))

medium

A. The slicing s[1:-1] is correct and no error exists

B. The function will cause infinite recursion

C. The base case should check for len(s) == 0 only

D. The comparison s[0] != s[-1] is incorrect

Solution

1. Step 1: Analyze base case and recursion

   Base case checks if string length is 1 or 0, which is correct for palindrome check.

2. Step 2: Check slicing and comparison

   Slicing s[1:-1] removes first and last characters correctly. Comparison s[0] != s[-1] correctly detects mismatch.

3. Final Answer:

   The slicing s[1:-1] is correct and no error exists -> Option A

4. Quick Check:

   Correct base case and slicing = no error [OK]

Hint: Check base case and slicing carefully [OK]

Common Mistakes:

• Thinking base case must be only empty string
• Assuming slicing causes infinite recursion
• Misreading character comparison

5. Given a list of strings, write a recursive function to return a new list containing only the strings that start with the letter 'a'. Which of these recursive approaches is correct?

hard

A. Check first string; if it starts with 'a', include it and recurse on rest; else recurse on rest without including it.

B. Loop through list and add strings starting with 'a' without recursion.

C. Return the original list without filtering.

D. Check last string only and ignore the rest.

Solution

1. Step 1: Understand recursive filtering

   Recursion should process one element and decide to include it or not, then recurse on the rest.

2. Step 2: Apply to strings starting with 'a'

   If first string starts with 'a', include it in result list plus recursive call on rest; else skip it and recurse on rest.

3. Final Answer:

   Check first string; if it starts with 'a', include it and recurse on rest; else recurse on rest without including it. -> Option A

4. Quick Check:

   Recursive filter = check first + recurse rest [OK]

Hint: Include first if matches, else skip, then recurse [OK]

Common Mistakes:

• Using loops instead of recursion
• Ignoring elements except last
• Returning unfiltered list