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

Time Complexity: Recursion on Arrays and Strings

O(n)

Understanding Time Complexity

When using recursion on arrays or strings, it is important to know how the number of steps grows as the input gets bigger.

We want to find out how many times the function calls itself and how that affects the total work done.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function sumArray(arr, index = 0) {
  if (index === arr.length) return 0;
  return arr[index] + sumArray(arr, index + 1);
}
    

This function adds all numbers in an array by calling itself for each element.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive call to sumArray for each element in the array.
• How many times: Once per element, so n times for an array of size n.

How Execution Grows With Input

Each element causes one recursive call, so the total steps grow directly with the number of elements.

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

Pattern observation: The work grows in a straight line as input size increases.

Final Time Complexity

Time Complexity: O(n)

This means the time to finish grows directly with the number of elements in the array.

Common Mistake

[X] Wrong: "Recursion always makes code slower by a lot, so it must be worse than loops."

[OK] Correct: Here, recursion visits each element once, just like a loop would, so the time is similar.

Interview Connect

Understanding how recursion works on arrays and strings helps you explain your code clearly and shows you can think about how fast it runs.

Self-Check

What if we changed the function to call itself twice for each element? How would the time complexity change?

Practice

1. What does a recursive function on an array typically do to process the array elements?

easy

A. It uses loops instead of calling itself.

B. It processes one element and calls itself on the rest of the array.

C. It processes all elements at once without calling itself.

D. It only processes the first and last elements.

Solution

1. Step 1: Understand recursion on arrays

   Recursive functions handle one element and then call themselves on the smaller part (rest of the array).

2. Step 2: Identify the typical recursive pattern

   This pattern reduces the problem size by one element each call until the array is empty.

3. Final Answer:

   It processes one element and calls itself on the rest of the array. -> Option B

4. Quick Check:

   Recursion = process one + recurse rest [OK]

Hint: Recursion breaks problem into smaller parts [OK]

Common Mistakes:

• Thinking recursion processes all elements at once
• Confusing recursion with loops
• Ignoring the base case

2. Which of the following is the correct syntax to define a recursive function in JavaScript that takes an array as input?

easy

A. function recurse(arr) { if(arr.length === 0) return; recurse(arr.slice(1)); }

B. function recurse(arr) { while(arr.length > 0) recurse(arr); }

C. function recurse(arr) { for(let i=0; i

D. function recurse(arr) { if(arr.length === 0) return; recurse(arr.pop()); }

Solution

1. Step 1: Check base case and recursive call

   function recurse(arr) { if(arr.length === 0) return; recurse(arr.slice(1)); } correctly checks if array is empty and calls itself with the rest of the array using slice(1).

2. Step 2: Identify incorrect syntax in other options

   The version using while(arr.length > 0) recurse(arr); causes infinite recursion because it passes the same array; the version using for loop calls recurse on individual elements; the version using arr.pop() passes a single element, not an array.

3. Final Answer:

   function recurse(arr) { if(arr.length === 0) return; recurse(arr.slice(1)); } -> Option A

4. Quick Check:

   Base case + recurse smaller array = correct syntax [OK]

Hint: Base case + smaller input slice needed [OK]

Common Mistakes:

• Missing base case causing infinite recursion
• Passing wrong argument type in recursive call
• Using loops inside recursion incorrectly

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

function sumArray(arr) {
  if (arr.length === 0) return 0;
  return arr[0] + sumArray(arr.slice(1));
}
console.log(sumArray([1, 2, 3, 4]));

medium

A. 1234

B. Error

C. undefined

D. 10

Solution

1. Step 1: Understand the recursive sum logic

   The function adds the first element to the sum of the rest recursively until array is empty.

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

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

3. Final Answer:

   10 -> Option D

4. Quick Check:

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

Hint: Sum = first element + sum of rest [OK]

Common Mistakes:

• Concatenating numbers as strings
• Forgetting base case returns 0
• Using arr.pop() which mutates array

4. Find the error in this recursive function that reverses a string:

function reverseStr(str) {
  if (str.length === 1) return str;
  return reverseStr(str.slice(1)) + str[0];
}
console.log(reverseStr('abc'));

medium

A. Base case should check for empty string, not length 1.

B. The recursive call should use str.slice(0, -1) instead of str.slice(1).

C. The function should return str[0] + reverseStr(str.slice(1)) instead.

D. No error, the function works correctly.

Solution

1. Step 1: Analyze base case condition

   Base case checks if string length is 1, but for empty string it should return empty string to avoid errors.

2. Step 2: Understand recursion on empty string

   If input is empty, function should return empty string to stop recursion safely.

3. Final Answer:

   Base case should check for empty string, not length 1. -> Option A

4. Quick Check:

   Base case empty string needed for safe recursion [OK]

Hint: Base case must handle empty string [OK]

Common Mistakes:

• Using wrong base case length
• Confusing slice indexes
• Assuming function works without base case

5. Given a nested array like [1, [2, [3, 4], 5], 6], which recursive approach correctly flattens it into [1, 2, 3, 4, 5, 6]?

hard

A. Return the original array as is without changes.

B. Use a loop to add elements without recursion.

C. Check if element is array, recursively flatten it, else add element to result.

D. Only flatten one level using slice and concat.

Solution

1. Step 1: Identify recursive flattening logic

   To flatten nested arrays, check each element: if array, recurse; else add to result.

2. Step 2: Understand why other options fail

   Loops alone can't flatten nested arrays fully; one-level flattening misses deeper nesting; returning original array does nothing.

3. Final Answer:

   Check if element is array, recursively flatten it, else add element to result. -> Option C

4. Quick Check:

   Recursive flatten = check array + recurse + add element [OK]

Hint: Recursively flatten nested arrays by checking element type [OK]

Common Mistakes:

• Flattening only one level
• Not checking if element is array
• Ignoring nested deeper arrays