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Table of Contents
Query operation efficiency comparison
Comparison of insertion and deletion operation efficiency
Memory usage and capacity expansion mechanism
Summary of usage suggestions
Home Java javaTutorial Difference between ArrayList and LinkedList?

Difference between ArrayList and LinkedList?

Jul 04, 2025 am 02:10 AM

ArrayList is suitable for frequent query, while LinkedList is suitable for frequent addition and deletion. ArrayList is implemented based on arrays, with a query time complexity of O(1), which is suitable for random access; LinkedList is implemented based on linked lists, with an insertion and deletion time complexity of O(1), but the efficiency is not high when traversing and positioning is required; ArrayList is continuously memory and has a default capacity of 10, and the expansion brings performance fluctuations, while each node of LinkedList occupies more memory; mainly random access is selected, and LinkedList is frequently added and deleted in the head or in the middle, and most scenarios prefer ArrayList to use, and then analyze and replace it when encountering performance bottlenecks.

Difference between ArrayList and LinkedList?

ArrayList and LinkedList are two commonly used List implementation classes in Java. Although they both implement List interfaces, there are obvious differences in underlying implementation, performance and applicable scenarios. Simply put: ArrayList is implemented based on arrays and is suitable for frequent queries; LinkedList is implemented based on linked lists and is suitable for frequent addition and deletion .


Query operation efficiency comparison

  • ArrayList accesses elements through indexes is very fast, and the time complexity is O(1), because it is based on an array structure and the memory is continuous.
  • LinkedList needs to start traversal and search from the beginning or end until the corresponding index is found, with the average time complexity of O(n).

For example: If you often want to get elements based on location (such as list.get(10000)), then ArrayList is obviously more efficient.


Comparison of insertion and deletion operation efficiency

  • When an ArrayList inserts or deletes elements in the middle, it needs to move the subsequent elements to maintain the continuity of the array, which will bring additional overhead, and the time complexity is O(n).
  • When inserting or deleting the LinkedList , it only needs to modify the references of the front and rear nodes, and does not need to move other elements. The time complexity is O(1) (provided that it has been positioned to that position).

However, it should be noted that if you use indexes to insert/delete, LinkedList needs to traverse to that location first, so the overall efficiency is not necessarily higher than ArrayList.


Memory usage and capacity expansion mechanism

  • ArrayList is a dynamic array with a default capacity of 10. It will automatically expand when elements exceed the current capacity (usually 1.5 times the original capacity). This scaling mechanism may cause performance fluctuations in some cases.
  • Each element of LinkedList is an independent node object. In addition to storing data, it also needs to save the predecessor and successor references, so each node occupies more memory than ArrayList.

If you are more sensitive to memory and the operation is mainly about adding and deleting, you can consider LinkedList; if it is mainly about reading more and writing less, ArrayList saves space and accesses faster.


Summary of usage suggestions

  • If your program mainly performs:
    • ? Lots of random access → Priority to ArrayList
    • ? Frequently insert/delete in the head or in the middle → prefer LinkedList
  • If you are not sure which one is better:
    • You can use ArrayList first, its performance is good enough in most scenarios
    • When you really encounter a performance bottleneck, you will do specific analysis and replacement

Basically that's it. The key to choosing which structure is still to look at the actual operation type and data scale.

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