1. Introduction

When working with dynamic collections in Java, the ArrayList class is often the first tool developers reach for. It provides a resizable array implementation that is both easy to use and performant in many scenarios.

According to Oracle:

“An ArrayList is a resizable array, which can be found in the java.util package.”

In this article, we explore the internal structure, performance characteristics, and practical use cases of ArrayList.

2. What is an ArrayList?

ArrayList is part of the Java Collections Framework and implements the List interface. Unlike traditional arrays, it grows automatically as new elements are added. It supports all the list operations and allows duplicate elements.

Key characteristics:

• Maintains insertion order
• Allows random access using indices
• Permits null elements
• Not synchronized (not thread-safe by default)

If you’re new to the Collections Framework, we recommend starting with our Introduction to Collections Framework in Java.

3. Internal Structure

Internally, an ArrayList is backed by a dynamic array. Initially, it allocates a default capacity (usually 10). When that capacity is exceeded, the array is resized—typically by increasing its size by 50%.

How resizing works:

1. A new array is created with larger capacity.
2. All existing elements are copied to the new array.
3. The old array is discarded.

This operation is costly (O(n)) and can affect performance if it happens frequently.

List<String> list = new ArrayList<>();
for (int i = 0; i < 100; i++) {
    list.add("Item " + i); // Resize occurs as needed
}

“An understanding of what happens under the hood can help you avoid performance pitfalls.”

4. Performance Analysis

Understanding time complexity is essential when choosing data structures. Here’s a breakdown of ArrayList operations:

Adding or removing elements at the end is fast, but doing so at the beginning or middle requires shifting elements—making it less efficient than LinkedList in those cases. For such situations, see our article on LinkedList in Java.

5. Practical Use Cases

ArrayList is ideal when:

• You need fast random access.
• You frequently add elements to the end.
• You don’t need thread safety.

Common applications include:

• Caching data for read-heavy operations
• Storing ordered results from a database query
• Backing a stack structure in single-threaded applications

6. Code Examples

Adding and Accessing Elements

To store elements in an ArrayList and retrieve them efficiently, you can use the add() method for insertion and the get() method for access. Below is a simple example that demonstrates how to add cities to an ArrayList and retrieve the first element:

List<String> cities = new ArrayList<>();
cities.add("Paris");
cities.add("London");
cities.add("New York");

System.out.println("First city: " + cities.get(0));

Iterating over Elements

To traverse through all elements in an ArrayList, you can use an enhanced for loop. This loop allows for clean and readable iteration over each item:

for (String city : cities) {
    System.out.println(city);
}

Removing an Element

To remove a specific item from an ArrayList, you can use the remove() method by specifying either the element itself or its index. The following example removes an element by its value:

cities.remove("London");
System.out.println("After removal: " + cities);

7. Limitations and Alternatives

While ArrayList is powerful, it has limitations:

• Poor performance for frequent insertions/removals at the beginning
• Not thread-safe

For multi-threaded scenarios, consider CopyOnWriteArrayList or synchronizing access manually. For heavy insert/remove operations in the middle of a list, LinkedList may be a better fit.

8. Conclusion

In summary, ArrayList offers an efficient and flexible way to store and manage data. Its predictable performance and ease of use make it a staple in Java development. Understanding its internal structure and limitations will help you make better decisions in your code.

“Choosing the right data structure is the first step toward efficient code.”

You can find the complete code of this article on GitHub.