When to use LinkedList over ArrayList in Java?

In Java, choosing between LinkedList and ArrayList depends on the specific use case and the operations you perform most frequently. Here’s a breakdown of when to prefer LinkedList over ArrayList:

When to Use LinkedList:

1. Frequent Insertions/Deletions in the Middle of the List

• Example: Adding/removing elements at arbitrary positions (not just the end).
• Why: LinkedList uses a doubly-linked list structure, so inserting/deleting nodes only requires updating pointers (O(1) for known positions).
• ArrayList Drawback: Shifting elements in an array takes O(n) time.

1. Frequent Use as a Queue, Deque, or Stack

• Example: Implementing FIFO (queue) or LIFO (stack) behavior.
• Why: LinkedList implements the Deque interface, supporting efficient O(1) operations like:
  • addFirst(), addLast(), removeFirst(), removeLast().
• Caveat: For pure queue/stack use, ArrayDeque is often faster and more memory-efficient than LinkedList.

1. Frequent Structural Modifications via Iterators

• Example: Iterating while adding/removing elements (e.g., with listIterator.add() or listIterator.remove()).
• Why: LinkedList allows in-place modifications during iteration without shifting elements (O(1) per operation).
• ArrayList Drawback: Modifying during iteration forces element shifts (O(n)).

When to Use ArrayList:

1. Frequent Random Access by Index

• Example: Accessing elements via get(index) or set(index).
• Why: ArrayList uses an array, so index-based access is O(1).
• LinkedList Drawback: Traversing nodes takes O(n) time.

1. Mostly Add/Remove at the End

• Example: Using the list as a dynamic array (e.g., appending elements).
• Why: ArrayList appends in amortized O(1) time (resizing is rare).
• LinkedList Drawback: Appending is O(1) but involves node creation overhead.

1. Memory Efficiency

• Why: ArrayList stores elements contiguously in memory, while LinkedList has overhead from node objects (storing next/prev pointers).

1. Faster Iteration

• Why: ArrayList leverages CPU cache locality for faster iteration.
• LinkedList Drawback: Nodes are scattered in memory, causing cache misses.

Performance Comparison

Operation	LinkedList	ArrayList
Insert/Delete (middle)	O(1) (with iterator)	O(n)
Add/Remove (end)	O(1)	Amortized O(1)
Random Access (get/set)	O(n)	O(1)
Memory Overhead	Higher (node objects)	Lower (contiguous array)

Example Use Cases

• Use LinkedList:
• Real-time chat applications where messages are frequently inserted/removed in the middle.
• Implementing a playlist with frequent song reordering.
• Custom data structures like graphs or adjacency lists.
• Use ArrayList:
• Storing and accessing database query results.
• Caching frequently accessed data with random lookups.
• Most general-purpose lists where reads dominate writes.

Key Takeaways

• Default to ArrayList for most use cases (better for random access, iteration, and memory).
• Choose LinkedList only when you need frequent mid-list modifications or deque-like behavior.
• Consider ArrayDeque over LinkedList for queue/stack operations (better performance).

By aligning your choice with the dominant operations, you optimize both time and space efficiency.