Fundamentals of Loop and Iteration in Programming

Iteration Introduction

To solve a problem, sometimes, we repeat a particular code statement several times until a specific condition is satisfied. It is known as iteration, which allows us to "write code once" and "execute many times." In computer programming, iteration is often referred to as ‘looping’ because instead of repeatedly writing the same code, we can execute the same code a finite number of times. It provides code reusability and simplifies steps of problem-solving. 

In data structure and algorithms, several problem-solving approaches are based on iteration. So a good grasp of the loop fundamental is essential for mastering these approaches. Here are some excellent examples of iterative problem-solving approaches:

  • Building partial solution using a single loop
  • Problem-solving using nested loop
  • Two pointers approach
  • Sliding window approach
  • Problem-solving using a hashing
  • Problem-solving using stack, queue, and Priority queue
  • BFS traversal in a tree and graph
  • The bottom-up approach of dynamic programming
  • Iterative backtracking using stack

Types of loops in programming

Iteration is implemented using the loop in programming languages, where we primarily use two types of loops: "for" loop and "while" loop.

'for' loop in programming

We use the "for" loop when we know how many times the loop will execute. In other words, the "for" loop helps us to run some particular code statement defined number of steps.

Inside the for loop, we use a loop variable to control the execution of the loop, where the initial value of the variable decides the starting point. So, we start by initializing the loop variable to some value and checking whether the loop condition is true or not. If the loop condition is true, the code inside the loop body will execute. Then, we update the loop variable and move to the next iteration. This step will be repeated till the loop condition becomes false.

for (loop initialisation; loop condition; loop update)
    loop body

'while' loop in programming

The "while" loop is used to execute the loop body until a specific condition is false. We mainly apply this idea when we don’t know how many times the loop will execute.

The while loop consists of a loop condition, a block of code as a loop body, and a loop update expression if required. First, the loop condition is evaluated, and if it is true, then the code within the loop body will be executed. This process repeats until the loop condition/expression becomes false. Thus, for better intuition, the while loop can be thought of as a repeating if statement.

loop initialisation
while (loop condition)
    loop body
    loop update

Special Notes

  • There is also a third type of loop in programming: the do-while loop. It is similar to the while loop, where loop execution is terminated based on some loop condition. But do-while loop condition is tested at the end of the loop body.
  • The do-while loop is exit controlled, whereas the for and while loops are entry controlled loops.
  • In the do-while loop, the loop body will execute at least once irrespective of the test condition. 
  • It's an exercise for you to explore the implementation and properties of the do-while loop.

For and while loop flowchart

Core elements of the loop in programming

  • Loop initialization: Initialization of the loop variables used before starting the first iteration of the loop execution.
  • Loop condition: This is a boolean expression calculated at the beginning of each loop iteration to determine whether the loop body will execute or stop.
  • Loop body: The core part of the loop where we perform required operations to manipulate data at each iteration. There can be more than one code statement here.
  • Loop update: We perform increment/decrement operations for the loop variable to control the repetitions of the loop.

So here is the basic flow of the loop execution:

  • Loop conditions will be evaluated first. 
  • If the loop condition is true, then the loop body will run, the loop variable gets updated (increment/decrement operation), and the loop condition's value is re-evaluated. The loop body will run as long as the loop condition will be true. 
  • As soon loop condition becomes false, we exit the loop and continue with the further code instructions.

How to design a correct iterative algorithm?

We should consider these critical steps to design and check the correctness of an iterative code in data structure and algorithms:

  • Pre-condition: must be appropriately defined and true before the loop executes. 
  • Post-condition: must be appropriately defined and true after the loop terminates.
  • Loop variant: An exit condition that controls the loop's execution must be appropriately defined to ensure loop termination.
  • Loop invariant: The most critical aspect that is true before and after each iteration of a loop. The values of variables may change, but the loop invariant's truth does not vary.

Let's try to understand the above idea via some examples.

Example 1: finding the sum of all integers from 1 to n

Pre-condition: we need to define two variables: a variable i that acts as a loop counter and a variable sum to store the sum of all integers. We would like to do a sum from 0 to n, so at the start, we initialize both variables to 0, i.e., sum = 0, i = 1

Post-condition: After the loop termination, the value of the sum must be equal to the sum of all integers from 1 to n.

Loop variant: The loop should terminate when we have added all integers from 1 to n,i.e, i<= n. In other words, the loop should not terminate until we have added n to the sum.

Loop invariant: Now, we need to set the loop invariant so that when the loop terminates, we will have the correct output. As discussed above, the loop invariant must be true before and after each loop iteration.

  • Before any ith iteration of the loop, the variable sum must be equal to the sum of all integers from 1 to i-1.
  • At the ith iteration, we add the value i to the sum (sum = sum + i) and increase the variable i by 1. This ensures that as we go through each iteration, the variable i would approach n and provide the sum of values from 1 to n after loop termination.
  • After the ith iteration, the variable sum must be equal to the sum of all integers from 1 to i.
  • The above invariant will continue till the end of the loop.

Solution Pseudocode

int findSum(int n)
    int i = 1
    int sum = 0
    while (i <= n) 
        sum = sum + i
        i = i + 1
    return sum

Example 2: Finding the max element in an array

Pre-condition: we need to define two variables: a loop variable i that acts as a loop counter and a variable max to store the maximum of all integers. Before starting the loop to find the max value from X[0] to X[n-1], we initialize max = X[0] and start the loop with i = 1. This pre-condition holds true when we enter the first iteration of the loop.

Post-condition: After the loop termination, the max value must store the max of all values from X[0] to X[n-1].

Loop variant: The loop must terminate after finding the max of all integers from X[0] to X[n-1]. In other words, the loop should not terminate until we have compared X[n-1] to the max i.e. i <= n-1 or i < n.

Loop invariant

Let's assume invariant is true after (i-1)th iteration, i.e., max store the maximum of all integers from X[0] to X[i-1]. We need to design instruction so that the invariant must be true after ith iterations of the loop - the variable max must be equal to the max of all integers from X[0] to X[i]. Here are the steps of the ith iteration:

  • We compare max with new value X[i]. If (max < X[i]), it means we have found a value that is greater than the max of all the values from X[0] to X[i-1]. In such a situation, we update the max value with X[i]i.e. max = X[i]. Otherwise, we ignore it, and the value stored in max is still the maximum of all integers from X[0] to X[i].
  • We also increase i by 1 through each iteration to update the maximum from X[0] to X[n-1] in the variable max.

Solution Pseudocode

int findMax(int X[], int n)
    int max = X[0]
    for (int i = 1; i < n; i = i + 1)
        if (X[i] > max)
            max = X[i]
    return max

Some common errors in writing loops 

Infinite loops

An infinite loop occurs when a loop condition continuously evaluates to true or not making progress towards loop termination. It appears most of the time due to the incorrect update of the loop variables or some error in the loop condition. Usually, this is an error, but it's common for infinite loops to occur accidentally.

For example, we want to display the sum of all numbers from 5 to 10 via the following code and ended up with an infinite loop because we did not increment the loop variable. The loop variable remains the same through each iteration, and progress is not made towards loop termination.

int i = 5
int sum = 0
while (i <= 10)
   sum = sum + i

Here is the correct version of the code:

int i = 5
int sum = 0
while (i <= 10) 
   sum = sum + i
   i = i + 1

Other examples of the Infinite loop

Example 1: For i < 0, this goes into an infinite loop!

void infinteLoop(int i)
    while (i != 0)
        i = i - 1 

Example 2: here loop condition is "1" which is always true!

int i = 0  
    i =  i + 1   

But in some situations, an infinite loop can be used on purpose. For example, we use an infinite loop for the applications that continuously accept the user input and constantly generate the output until the user comes out of the application manually.

  • An operating system is the best example of it. It runs in an infinite loop and performs tasks continuously. It only comes out of an infinite loop when the user manually shuts down the system.
  • We read from input a sequence of data and stop reading from the input as soon as a particular condition becomes true. The general structure of an input loop:

    read the first element 
    while (element is valid) 
      process the element 
      read the following element 
  • Some online games execute in an infinite loop. The game will keep accepting the user requests until the user exits from the game.
  • A typical web server runs in an infinite loop as the server responds to all the client requests. It takes a request for a web page, returns a web page, and waits for the subsequent request. It will come out of an indefinite loop only when the admin shuts down the server manually.

    while (true)
      Read request
      Process request
    Another popular way is:
    for ( ; ; )
      Read request
      Process request

Off-By-One error in the loop

It is an error involving the boundary condition of the loop: the loop variable's initial value or the loop's end condition. This problem could arise when a programmer makes mistakes such as: 

  • Using <=" instead of "<" while checking the expression in the loop condition.
  • Fails to consider a sequence that starts at zero rather than one.

Off-By-One Example 1

int X[5]
for (int i = 0; i <= 5; i = i + 1)

The above program will result in an array out of bounds exception because we will try to display the result for X[5] and the upper bound of the array is only 4. This is because the index for the array starts at 0 instead of 1 in most programming languages. The correct code is displayed below.

int X[5]
for (int i = 0; i < 5; i = i + 1)

Off-By-One Example 2

  • Case1: for (int i = 1; i < n; i = i + 1) { ... }
  • Case2: for (int i = 0; i <= n; i = i + 1) { ... }

In the first case, the loop will be executed (n-1) times and in the second case (n + 1) times, giving error off-by-one. The loop can be written correctly as: for (int i = 0; i < n; i = i + 1) { ... }

Examples of Various Loops

Single loop increasing by 1

Loop of finding the nth Fibonacci using the bottom-up approach of DP

for(int i = 2; i <= n; i = i + 1)
    Fib[i] = Fib[i - 1] + Fib[i - 2]

Kadane algorithm loop of finding maximum subarray sum

for (i = 1; i < n; i = i + 1)
    curr_maxSum = max (curr_maxSum + X[i], X[i])
    if(maxSum < curr_maxSum)
        maxSum = curr_maxSum

Boyer–Moore voting algorithm of finding majority element in an array

for(int i = 0; i < n; i = i + 1) 
    if(count == 0) 
        majorityCandidate = X[i]
    if(X[i] == majorityCandidate) 
        count = count + 1
        count = count - 1

Nested loops

Nested loop of the Bubble sort algorithm

for(int i = 0; i < n; i = i + 1)
    for(int j = 0; j < n - i - 1; j = j + 1)
        if( X[j] > X[j+1])
            temp = A[j]
            X[j] = X[j+1]
            X[j+1] = temp

Nested loop of the Insertion sort algorithm

for(int i = 1; i < n - 1; i = i + 1) 
    int key = X[i]
    int j = i - 1  
    while (j >= 0 && X[j] > key) 
        X[j + 1] = X[j]
        j = j - 1 
    X[j + 1] = key

Nested loop of finding transpose of a square matrix

for (int i = 0; i < n; i = i + 1)
    for (int j = i + 1; j < n; j + 1)
        swap(X[i][j], X[j][i])

Single loop increasing by 2

A single loop of finding max and min in an array

while (i < n)
    if (X[i] < X[i+1])
        if (X[i] < min)
            min = X[i]
        if (X[i+1] > max)
            max = X[i+1]
        if (X[i] > max)
            max = X[i]
        if (X[i+1] < min)
            min = X[i+1] 
    i = i + 2

Single loop of sorting an array in a waveform

for (int i = 0; i < n; i = i + 2)
    if (i > 0 && X[i-1] > X[i])
        swap(X[i], X[i-1])
    if (i < n-1 && X[i] < X[i+1])
        swap(X[i], X[i + 1])

Single loop Increasing or decreasing by a factor of 2

Loop of exponential search in an unbounded array

while (i < n && X[i] <= key)
    i = i*2

Loop of iterative Binary Search

while (left <= right) 
    int mid = left + (right - left)/2
    if (X[mid] == key)
        return mid       
    if (X[mid] < key)
        left = mid + 1      
        right = mid - 1

Loop of searching iteratively in a BST

while (root != NULL) 
    if (key < root->data)
        root = root->left
    else if (key > root->data)
        root = root->right
        return true

Two pointers loop: pointers moving in the opposite direction

Two-pointers loop of reversing an array

while (left < right)
    int temp = X[left]
    X[left] = X[right]
    X[right] = temp
    left = left + 1
    right = right - 1

Two pointers loop of finding pair sum in a sorted array

while (l < r)
    if(X[l] + X[r] == k)
        return 1
    else if(X[l] + X[r] < k)
        l = l + 1
        r = r - 1

Two pointers loop: pointers moving in the same direction

Two-pointers loop of merging algorithm in merge sort

while (i < n1 && j < n2) 
    if (X[i] <= Y[j]) 
        A[k] = X[i]
        i = i + 1
        A[k] = Y[j]
        j = j + 1
    k = k + 1

Two-pointers loop of partition algorithm in quicksort

for (int j = left; j < right; j = j + 1)
    if (x[j] < pivot)
        i = i + 1
        swap(X[i], X[j])

Two-pointers loop of finding loop in a linked list: Floyd algorithm

while (slow && fast && fast->next) 
    slow = slow->next
    fast = fast->next->next
    if (slow == fast)
        return 1

Loop on stack and queue data structures

BFS Traversal of binary tree using queue

while (Q.empty() == false)
    TreeNode temp = Q.dequeue()
    if (temp->left != NULL)
    if (temp->right != NULL)

Pre-order traversal in binary search using stack

while (S.empty() == false)
    Treenode temp = S.pop()
    if (temp->right)
    if (temp->left)

Critical ideas to think!

  • Sometimes we forget to initialize and update the variable used in the condition of the loop. This is a serious programming error.
  • Although loops typically iterate over only one variable, sometimes for loops need to work with multiple variables.
  • When we declare a variable inside a loop, the scope of that variable ends with the end of the loop statement. In other words, the scope of the loop variable is inside the loop, and it can not be accessed from outside the loop.

    int w
    // we can use x or w inside ()
    for(int x = 0; x < 5; x = x + 1) 
      int y
      // we can use x, y, w here
    int z 
    // we can only use w, z here; 
    x and y are only visible in the scope of the loop.

Critical concepts to explore in Loop

  • Break and Continue loop statements
  • Two pointers and sliding window approach
  • The idea of iterator in data structure
  • Iteration vs. Recursion comparison
  • Iterative problem-solving approaches
  • Time complexity analysis of various loops

Coding problems to practice using loop

  • Convert roman to integer
  • Fizz Buzz Problem
  • Look-and-Say Sequence
  • Move zeroes to an end
  • Merge two sorted array
  • max and min of an array
  • Print a given matrix in spiral form
  • Rotate a matrix by 90 degrees

Enjoy learning, Enjoy coding, Enjoy algorithms!

More From EnjoyAlgorithms

Our weekly newsletter

Subscribe to get free weekly content on data structure and algorithms, machine learning, system design, oops design and mathematics.

Follow Us:


© 2020 EnjoyAlgorithms Inc.

All rights reserved.