When to Use Linkedlist over Arraylist in Java?

David Miller
David Miller
• • 34 min read

I've Always Been One to Simply Use: List Names = New Arraylist(); I Use the Interface as the Type Name for Portability, So That When I Ask Questions Such as...

When to Use Linkedlist over Arraylist in Java?

I've always been one to simply use:

List<String> names = new ArrayList<>();

I use the interface as the type name for portability, so that when I ask questions such as this, I can rework my code.

When should LinkedList be used over ArrayList and vice-versa?

3

33 Answers

1
2

Summary ArrayList with ArrayDeque are preferable in many more use-cases than LinkedList. If you're not sure — just start with ArrayList.

TLDR, in ArrayList accessing an element takes constant time [O(1)] and adding an element takes O(n) time [worst case]. In LinkedList inserting an element takes O(n) time and accessing also takes O(n) time but LinkedList uses more memory than ArrayList.

LinkedList and ArrayList are two different implementations of the List interface. LinkedList implements it with a doubly-linked list. ArrayList implements it with a dynamically re-sizing array.

As with standard linked list and array operations, the various methods will have different algorithmic runtimes.

For LinkedList<E>

  • get(int index) is O(n) (with n/4 steps on average), but O(1) when index = 0 or index = list.size() - 1 (in this case, you can also use getFirst() and getLast()). One of the main benefits of LinkedList<E>
  • add(int index, E element) is O(n) (with n/4 steps on average), but O(1) when index = 0 or index = list.size() - 1 (in this case, you can also use addFirst() and addLast()/add()). One of the main benefits of LinkedList<E>
  • remove(int index) is O(n) (with n/4 steps on average), but O(1) when index = 0 or index = list.size() - 1 (in this case, you can also use removeFirst() and removeLast()). One of the main benefits of LinkedList<E>
  • Iterator.remove() is O(1). One of the main benefits of LinkedList<E>
  • ListIterator.add(E element) is O(1). One of the main benefits of LinkedList<E>

Note: Many of the operations need n/4 steps on average, constant number of steps in the best case (e.g. index = 0), and n/2 steps in worst case (middle of list)

For ArrayList<E>

  • get(int index) is O(1). Main benefit of ArrayList<E>
  • add(E element) is O(1) amortized, but O(n) worst-case since the array must be resized and copied
  • add(int index, E element) is O(n) (with n/2 steps on average)
  • remove(int index) is O(n) (with n/2 steps on average)
  • Iterator.remove() is O(n) (with n/2 steps on average)
  • ListIterator.add(E element) is O(n) (with n/2 steps on average)

Note: Many of the operations need n/2 steps on average, constant number of steps in the best case (end of list), n steps in the worst case (start of list)

LinkedList<E> allows for constant-time insertions or removals using iterators, but only sequential access of elements. In other words, you can walk the list forwards or backwards, but finding a position in the list takes time proportional to the size of the list. Javadoc says "operations that index into the list will traverse the list from the beginning or the end, whichever is closer", so those methods are O(n) (n/4 steps) on average, though O(1) for index = 0.

ArrayList<E>, on the other hand, allow fast random read access, so you can grab any element in constant time. But adding or removing from anywhere but the end requires shifting all the latter elements over, either to make an opening or fill the gap. Also, if you add more elements than the capacity of the underlying array, a new array (1.5 times the size) is allocated, and the old array is copied to the new one, so adding to an ArrayList is O(n) in the worst case but constant on average.

So depending on the operations you intend to do, you should choose the implementations accordingly. Iterating over either kind of List is practically equally cheap. (Iterating over an ArrayList is technically faster, but unless you're doing something really performance-sensitive, you shouldn't worry about this -- they're both constants.)

The main benefits of using a LinkedList arise when you re-use existing iterators to insert and remove elements. These operations can then be done in O(1) by changing the list locally only. In an array list, the remainder of the array needs to be moved (i.e. copied). On the other side, seeking in a LinkedList means following the links in O(n) (n/2 steps) for worst case, whereas in an ArrayList the desired position can be computed mathematically and accessed in O(1).

Another benefit of using a LinkedList arises when you add or remove from the head of the list, since those operations are O(1), while they are O(n) for ArrayList. Note that ArrayDeque may be a good alternative to LinkedList for adding and removing from the head, but it is not a List.

Also, if you have large lists, keep in mind that memory usage is also different. Each element of a LinkedList has more overhead since pointers to the next and previous elements are also stored. ArrayLists don't have this overhead. However, ArrayLists take up as much memory as is allocated for the capacity, regardless of whether elements have actually been added.

The default initial capacity of an ArrayList is pretty small (10 from Java 1.4 - 1.8). But since the underlying implementation is an array, the array must be resized if you add a lot of elements. To avoid the high cost of resizing when you know you're going to add a lot of elements, construct the ArrayList with a higher initial capacity.

If the data structures perspective is used to understand the two structures, a LinkedList is basically a sequential data structure which contains a head Node. The Node is a wrapper for two components : a value of type T [accepted through generics] and another reference to the Node linked to it. So, we can assert it is a recursive data structure (a Node contains another Node which has another Node and so on...). Addition of elements takes linear time in LinkedList as stated above.

An ArrayList is a growable array. It is just like a regular array. Under the hood, when an element is added, and the ArrayList is already full to capacity, it creates another array with a size which is greater than previous size. The elements are then copied from previous array to new one and the elements that are to be added are also placed at the specified indices.

6

Thus far, nobody seems to have addressed the memory footprint of each of these lists besides the general consensus that a LinkedList is "lots more" than an ArrayList so I did some number crunching to demonstrate exactly how much both lists take up for N null references.

Since references are either 32 or 64 bits (even when null) on their relative systems, I have included 4 sets of data for 32 and 64 bit LinkedLists and ArrayLists.

Note: The sizes shown for the ArrayList lines are for trimmed lists - In practice, the capacity of the backing array in an ArrayList is generally larger than its current element count.

Note 2: (thanks BeeOnRope) As CompressedOops is default now from mid JDK6 and up, the values below for 64-bit machines will basically match their 32-bit counterparts, unless of course you specifically turn it off.

The result clearly shows that LinkedList is a whole lot more than ArrayList, especially with a very high element count. If memory is a factor, steer clear of LinkedLists.

The formulas I used follow, let me know if I have done anything wrong and I will fix it up. 'b' is either 4 or 8 for 32 or 64 bit systems, and 'n' is the number of elements. Note the reason for the mods is because all objects in java will take up a multiple of 8 bytes space regardless of whether it is all used or not.

ArrayList:

ArrayList object header + size integer + modCount integer + array reference + (array oject header + b * n) + MOD(array oject, 8) + MOD(ArrayList object, 8) == 8 + 4 + 4 + b + (12 + b * n) + MOD(12 + b * n, 8) + MOD(8 + 4 + 4 + b + (12 + b * n) + MOD(12 + b * n, 8), 8)

LinkedList:

LinkedList object header + size integer + modCount integer + reference to header + reference to footer + (node object overhead + reference to previous element + reference to next element + reference to element) * n) + MOD(node object, 8) * n + MOD(LinkedList object, 8) == 8 + 4 + 4 + 2 * b + (8 + 3 * b) * n + MOD(8 + 3 * b, 8) * n + MOD(8 + 4 + 4 + 2 * b + (8 + 3 * b) * n + MOD(8 + 3 * b, 8) * n, 8)

1

ArrayList is what you want. LinkedList is almost always a (performance) bug.

Why LinkedList sucks:

  • It uses lots of small memory objects, and therefore impacts performance across the process.
  • Lots of small objects are bad for cache-locality.
  • Any indexed operation requires a traversal, i.e. has O(n) performance. This is not obvious in the source code, leading to algorithms O(n) slower than if ArrayList was used.
  • Getting good performance is tricky.
  • Even when big-O performance is the same as ArrayList, it is probably going to be significantly slower anyway.
  • It's jarring to see LinkedList in source because it is probably the wrong choice.
Algorithm           ArrayList   LinkedList
seek front            O(1)         O(1)
seek back             O(1)         O(1)
seek to index         O(1)         O(N)
insert at front       O(N)         O(1)
insert at back        O(1)         O(1)
insert after an item  O(N)         O(1)

Algorithms: Big-Oh Notation (archived)

ArrayLists are good for write-once-read-many or appenders, but bad at add/remove from the front or middle.

12

As someone who has been doing operational performance engineering on very large scale SOA web services for about a decade, I would prefer the behavior of LinkedList over ArrayList. While the steady-state throughput of LinkedList is worse and therefore might lead to buying more hardware -- the behavior of ArrayList under pressure could lead to apps in a cluster expanding their arrays in near synchronicity and for large array sizes could lead to lack of responsiveness in the app and an outage, while under pressure, which is catastrophic behavior.

Similarly, you can get better throughput in an app from the default throughput tenured garbage collector, but once you get java apps with 10GB heaps you can wind up locking up the app for 25 seconds during a Full GCs which causes timeouts and failures in SOA apps and blows your SLAs if it occurs too often. Even though the CMS collector takes more resources and does not achieve the same raw throughput, it is a much better choice because it has more predictable and smaller latency.

ArrayList is only a better choice for performance if all you mean by performance is throughput and you can ignore latency. In my experience at my job I cannot ignore worst-case latency.

Update (Aug 27, 2021 -- 10 years later): This answer (my most historically upvoted answer on SO as well) is very likely wrong (for reasons outlined in the comments below). I'd like to add that ArrayList will optimize for sequential reading of memory and minimize cache-line and TLB misses, etc. The copying overhead when the array grows past the bounds is likely inconsequential by comparison (and can be done by efficient CPU operations). This answer is also probably getting worse over time given hardware trends. The only situations where a LinkedList might make sense would be something highly contrived where you had thousands of Lists any one of which might grow to be GB-sized, but where no good guess could be made at allocation-time of the List and setting them all to GB-sized would blow up the heap. And if you found some problem like that, then it really does call for reengineering whatever your solution is (and I don't like to lightly suggest reengineering old code because I myself maintain piles and piles of old code, but that'd be a very good case of where the original design has simply run out of runway and does need to be chucked). I'll still leave my decades-old poor opinion up there for you to read though. Simple, logical and pretty wrong.

7

Yeah, I know, this is an ancient question, but I'll throw in my two cents:

LinkedList is almost always the wrong choice, performance-wise. There are some very specific algorithms where a LinkedList is called for, but those are very, very rare and the algorithm will usually specifically depend on LinkedList's ability to insert and delete elements in the middle of the list relatively quickly, once you've navigated there with a ListIterator.

There is one common use case in which LinkedList outperforms ArrayList: that of a queue. However, if your goal is performance, instead of LinkedList you should also consider using an ArrayBlockingQueue (if you can determine an upper bound on your queue size ahead of time, and can afford to allocate all the memory up front), or this CircularArrayList implementation. (Yes, it's from 2001, so you'll need to generify it, but I got comparable performance ratios to what's quoted in the article just now in a recent JVM)

6

Joshua Bloch, the author of LinkedList:

Does anyone actually use LinkedList? I wrote it, and I never use it.

Link:

I'm sorry for the answer not being as informative as the other answers, but I thought it would be the most self-explanatory if not revealing.

0

It's an efficiency question. LinkedList is fast for adding and deleting elements, but slow to access a specific element. ArrayList is fast for accessing a specific element but can be slow to add to either end, and especially slow to delete in the middle.

Array vs ArrayList vs LinkedList vs Vector goes more in depth, as does Linked List.

2

Correct or Incorrect: Please execute test locally and decide for yourself!

Edit/Remove is faster in LinkedList than ArrayList.

ArrayList, backed by Array, which needs to be double the size, is worse in large volume application.

Below is the unit test result for each operation.Timing is given in Nanoseconds.

Operation                       ArrayList                      LinkedList  

AddAll   (Insert)               101,16719                      2623,29291 

Add      (Insert-Sequentially)  152,46840                      966,62216

Add      (insert-randomly)      36527                          29193

remove   (Delete)               20,56,9095                     20,45,4904

contains (Search)               186,15,704                     189,64,981

Here's the code:

import org.junit.Assert;
import org.junit.Test;

import java.util.*;

public class ArrayListVsLinkedList {
    private static final int MAX = 500000;
    String[] strings = maxArray();

    ////////////// ADD ALL ////////////////////////////////////////
    @Test
    public void arrayListAddAll() {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> arrayList = new ArrayList<String>(MAX);

        watch.start();
        arrayList.addAll(stringList);
        watch.totalTime("Array List addAll() = ");//101,16719 Nanoseconds
    }

    @Test
    public void linkedListAddAll() throws Exception {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);

        watch.start();
        List<String> linkedList = new LinkedList<String>();
        linkedList.addAll(stringList);
        watch.totalTime("Linked List addAll() = ");  //2623,29291 Nanoseconds
    }

    //Note: ArrayList is 26 time faster here than LinkedList for addAll()

    ///////////////// INSERT /////////////////////////////////////////////
    @Test
    public void arrayListAdd() {
        Watch watch = new Watch();
        List<String> arrayList = new ArrayList<String>(MAX);

        watch.start();
        for (String string : strings)
            arrayList.add(string);
        watch.totalTime("Array List add() = ");//152,46840 Nanoseconds
    }

    @Test
    public void linkedListAdd() {
        Watch watch = new Watch();

        List<String> linkedList = new LinkedList<String>();
        watch.start();
        for (String string : strings)
            linkedList.add(string);
        watch.totalTime("Linked List add() = ");  //966,62216 Nanoseconds
    }

    //Note: ArrayList is 9 times faster than LinkedList for add sequentially

    /////////////////// INSERT IN BETWEEN ///////////////////////////////////////

    @Test
    public void arrayListInsertOne() {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> arrayList = new ArrayList<String>(MAX + MAX / 10);
        arrayList.addAll(stringList);

        String insertString0 = getString(true, MAX / 2 + 10);
        String insertString1 = getString(true, MAX / 2 + 20);
        String insertString2 = getString(true, MAX / 2 + 30);
        String insertString3 = getString(true, MAX / 2 + 40);

        watch.start();

        arrayList.add(insertString0);
        arrayList.add(insertString1);
        arrayList.add(insertString2);
        arrayList.add(insertString3);

        watch.totalTime("Array List add() = ");//36527
    }

    @Test
    public void linkedListInsertOne() {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> linkedList = new LinkedList<String>();
        linkedList.addAll(stringList);

        String insertString0 = getString(true, MAX / 2 + 10);
        String insertString1 = getString(true, MAX / 2 + 20);
        String insertString2 = getString(true, MAX / 2 + 30);
        String insertString3 = getString(true, MAX / 2 + 40);

        watch.start();

        linkedList.add(insertString0);
        linkedList.add(insertString1);
        linkedList.add(insertString2);
        linkedList.add(insertString3);

        watch.totalTime("Linked List add = ");//29193
    }


    //Note: LinkedList is 3000 nanosecond faster than ArrayList for insert randomly.

    ////////////////// DELETE //////////////////////////////////////////////////////
    @Test
    public void arrayListRemove() throws Exception {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> arrayList = new ArrayList<String>(MAX);

        arrayList.addAll(stringList);
        String searchString0 = getString(true, MAX / 2 + 10);
        String searchString1 = getString(true, MAX / 2 + 20);

        watch.start();
        arrayList.remove(searchString0);
        arrayList.remove(searchString1);
        watch.totalTime("Array List remove() = ");//20,56,9095 Nanoseconds
    }

    @Test
    public void linkedListRemove() throws Exception {
        Watch watch = new Watch();
        List<String> linkedList = new LinkedList<String>();
        linkedList.addAll(Arrays.asList(strings));

        String searchString0 = getString(true, MAX / 2 + 10);
        String searchString1 = getString(true, MAX / 2 + 20);

        watch.start();
        linkedList.remove(searchString0);
        linkedList.remove(searchString1);
        watch.totalTime("Linked List remove = ");//20,45,4904 Nanoseconds
    }

    //Note: LinkedList is 10 millisecond faster than ArrayList while removing item.

    ///////////////////// SEARCH ///////////////////////////////////////////
    @Test
    public void arrayListSearch() throws Exception {
        Watch watch = new Watch();
        List<String> stringList = Arrays.asList(strings);
        List<String> arrayList = new ArrayList<String>(MAX);

        arrayList.addAll(stringList);
        String searchString0 = getString(true, MAX / 2 + 10);
        String searchString1 = getString(true, MAX / 2 + 20);

        watch.start();
        arrayList.contains(searchString0);
        arrayList.contains(searchString1);
        watch.totalTime("Array List addAll() time = ");//186,15,704
    }

    @Test
    public void linkedListSearch() throws Exception {
        Watch watch = new Watch();
        List<String> linkedList = new LinkedList<String>();
        linkedList.addAll(Arrays.asList(strings));

        String searchString0 = getString(true, MAX / 2 + 10);
        String searchString1 = getString(true, MAX / 2 + 20);

        watch.start();
        linkedList.contains(searchString0);
        linkedList.contains(searchString1);
        watch.totalTime("Linked List addAll() time = ");//189,64,981
    }

    //Note: Linked List is 500 Milliseconds faster than ArrayList

    class Watch {
        private long startTime;
        private long endTime;

        public void start() {
            startTime = System.nanoTime();
        }

        private void stop() {
            endTime = System.nanoTime();
        }

        public void totalTime(String s) {
            stop();
            System.out.println(s + (endTime - startTime));
        }
    }


    private String[] maxArray() {
        String[] strings = new String[MAX];
        Boolean result = Boolean.TRUE;
        for (int i = 0; i < MAX; i++) {
            strings[i] = getString(result, i);
            result = !result;
        }
        return strings;
    }

    private String getString(Boolean result, int i) {
        return String.valueOf(result) + i + String.valueOf(!result);
    }
}
13

ArrayList is essentially an array. LinkedList is implemented as a double linked list.

The get is pretty clear. O(1) for ArrayList, because ArrayList allow random access by using index. O(n) for LinkedList, because it needs to find the index first. Note: there are different versions of add and remove.

LinkedList is faster in add and remove, but slower in get. In brief, LinkedList should be preferred if:

  1. there are no large number of random access of element
  2. there are a large number of add/remove operations

=== ArrayList ===

  • add(E e)
    • add at the end of ArrayList
    • require memory resizing cost.
    • O(n) worst, O(1) amortized
  • add(int index, E element)
    • add to a specific index position
    • require shifting & possible memory resizing cost
    • O(n)
  • remove(int index)
    • remove a specified element
    • require shifting & possible memory resizing cost
    • O(n)
  • remove(Object o)
    • remove the first occurrence of the specified element from this list
    • need to search the element first, and then shifting & possible memory resizing cost
    • O(n)

=== LinkedList ===

  • add(E e)

    • add to the end of the list
    • O(1)

  • add(int index, E element)

    • insert at specified position
    • need to find the position first
    • O(n)
  • remove()
    • remove first element of the list
    • O(1)
  • remove(int index)
    • remove element with specified index
    • need to find the element first
    • O(n)
  • remove(Object o)
    • remove the first occurrence of the specified element
    • need to find the element first
    • O(n)

Here is a figure from programcreek.com (add and remove are the first type, i.e., add an element at the end of the list and remove the element at the specified position in the list.):

1

TL;DR due to modern computer architecture, ArrayList will be significantly more efficient for nearly any possible use-case - and therefore LinkedList should be avoided except some very unique and extreme cases.

In theory, LinkedList has an O(1) for the add(E element)

Also adding an element in the mid of a list should be very efficient.

Practice is very different, as LinkedList is a Cache Hostile Data structure. From performance POV - there are very little cases where LinkedList could be better performing than the Cache-friendly ArrayList.

Here are results of a benchmark testing inserting elements in random locations. As you can see - the array list if much more efficient, although in theory each insert in the middle of the list will require "move" the n later elements of the array (lower values are better):

Working on a later generation hardware (bigger, more efficient caches) - the results are even more conclusive:

LinkedList takes much more time to accomplish the same job. source Source Code

There are two main reasons for this:

  1. Mainly - that the nodes of the LinkedList are scattered randomly across the memory. RAM ("Random Access Memory") isn't really random and blocks of memory need to be fetched to cache. This operation takes time, and when such fetches happen frequently - the memory pages in the cache need to be replaced all the time -> Cache misses -> Cache is not efficient. ArrayList elements are stored on continuous memory - which is exactly what the modern CPU architecture is optimizing for.

  2. Secondary LinkedList required to hold back/forward pointers, which means 3 times the memory consumption per value stored compared to ArrayList.

DynamicIntArray, btw, is a custom ArrayList implementation holding Int (primitive type) and not Objects - hence all data is really stored adjacently - hence even more efficient.

A key elements to remember is that the cost of fetching memory block, is more significant than the cost accessing a single memory cell. That's why reader 1MB of sequential memory is up to x400 times faster than reading this amount of data from different blocks of memory:

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD
Read 1 MB sequentially from memory     250,000   ns      250 us
Round trip within same datacenter      500,000   ns      500 us
Read 1 MB sequentially from SSD*     1,000,000   ns    1,000 us    1 ms  ~1GB/sec SSD, 4X memory
Disk seek                           10,000,000   ns   10,000 us   10 ms  20x datacenter roundtrip
Read 1 MB sequentially from disk    20,000,000   ns   20,000 us   20 ms  80x memory, 20X SSD
Send packet CA->Netherlands->CA    150,000,000   ns  150,000 us  150 ms

Source: Latency Numbers Every Programmer Should Know

Just to make the point even clearer, please check the benchmark of adding elements to the beginning of the list. This is a use-case where, in-theory, the LinkedList should really shine, and ArrayList should present poor or even worse-case results:

Note: this is a benchmark of the C++ Std lib, but my previous experience shown the C++ and Java results are very similar. Source Code

Copying a sequential bulk of memory is an operation optimized by the modern CPUs - changing theory and actually making, again, ArrayList/Vector much more efficient

Credits: All benchmarks posted here are created by Kjell Hedström. Even more data can be found on his blog

3

ArrayList is randomly accessible, while LinkedList is really cheap to expand and remove elements from. For most cases, ArrayList is fine.

Unless you've created large lists and measured a bottleneck, you'll probably never need to worry about the difference.

9

If your code has add(0) and remove(0), use a LinkedList and it's prettier addFirst() and removeFirst() methods. Otherwise, use ArrayList.

And of course, Guava's ImmutableList is your best friend.

4

I usually use one over the other based on the time complexities of the operations that I'd perform on that particular List. 

|---------------------|---------------------|--------------------|------------|
|      Operation      |     ArrayList       |     LinkedList     |   Winner   |
|---------------------|---------------------|--------------------|------------|
|     get(index)      |       O(1)          |         O(n)       | ArrayList  |
|                     |                     |  n/4 steps in avg  |            |
|---------------------|---------------------|--------------------|------------|
|      add(E)         |       O(1)          |         O(1)       | LinkedList |
|                     |---------------------|--------------------|            |
|                     | O(n) in worst case  |                    |            |
|---------------------|---------------------|--------------------|------------|
|    add(index, E)    |       O(n)          |         O(n)       | LinkedList |
|                     |     n/2 steps       |      n/4 steps     |            |
|                     |---------------------|--------------------|            |
|                     |                     |  O(1) if index = 0 |            |
|---------------------|---------------------|--------------------|------------|
|  remove(index, E)   |       O(n)          |         O(n)       | LinkedList |
|                     |---------------------|--------------------|            |
|                     |     n/2 steps       |      n/4 steps     |            |
|---------------------|---------------------|--------------------|------------|
|  Iterator.remove()  |       O(n)          |         O(1)       | LinkedList |
|  ListIterator.add() |                     |                    |            |
|---------------------|---------------------|--------------------|------------|


|--------------------------------------|-----------------------------------|
|              ArrayList               |            LinkedList             |
|--------------------------------------|-----------------------------------|
|     Allows fast read access          |   Retrieving element takes O(n)   |
|--------------------------------------|-----------------------------------|
|   Adding an element require shifting | o(1) [but traversing takes time]  |
|       all the later elements         |                                   |
|--------------------------------------|-----------------------------------|
|   To add more elements than capacity |
|    new array need to be allocated    |
|--------------------------------------|
1

Let's compare LinkedList and ArrayList w.r.t. below parameters:

Must Read

1. Implementation

ArrayList is the resizable array implementation of list interface , while

LinkedList is the Doubly-linked list implementation of the list interface.

David Miller

David Miller

Executive Financial & Market Analyst
Twitter Linkedin Medium

David Miller brings 15 years of experience in global economics, personal finance strategy, and market dynamics. He specializes in turning complex economic trends into actionable insights for everyday readers.