What Is Underflow and Overflow Condition in Data Structure?


Larry Thompson

When working with data structures, it is important to be aware of potential issues that can arise. Two such issues are underflow and overflow conditions. In this article, we will explore what these conditions are and how they can impact our data structures.

What is Underflow?

Underflow occurs when we try to remove an element from an empty data structure. For example, let’s consider a stack data structure. A stack follows the Last-In-First-Out (LIFO) principle, where the most recently added element is the first one to be removed.

If we attempt to pop an element from an empty stack, it will result in underflow. This situation can lead to errors or unexpected behavior in our program.


        Stack myStack = new Stack();
        myStack.pop(); // Underflow error!

What is Overflow?

Overflow, on the other hand, occurs when we try to add an element to a data structure that is already full. Let’s consider an array as a simple example of a data structure with a fixed size.

If we attempt to insert an element into a full array, it will result in overflow. This situation can cause data loss or corruption and may lead to program crashes or other undesired outcomes.


        int[] myArray = new int[5];
        for (int i = 0; i <= 5; i++) {
            myArray[i] = i; // Overflow error!

Preventing Underflow and Overflow

To prevent underflow, we should always check if a data structure is empty before performing any removal operations. In our stack example, we can use the isEmpty() method to check if the stack is empty before popping an element.

To prevent overflow, we should ensure that our data structure has enough capacity to accommodate the elements we plan to insert. If using a fixed-size data structure like an array, we must be mindful of its size limitations and avoid trying to insert more elements than it can hold.


Understanding underflow and overflow conditions is crucial when working with data structures. By being aware of these issues and implementing proper checks and safeguards in our code, we can prevent errors and ensure the integrity of our data. Remember to always check for underflow before removing elements and avoid overflow by ensuring sufficient capacity in our data structures.

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