ArrayList Vs LinkedList in Java

ArrayList and LinkedList are two prominent classes in the Collection framework, each proficiently implementing the List interface. The LinkedList class ingeniously accomplishes this by employing a doubly-linked list, enabling efficient insertion and removal operations. On the other hand, the ArrayList class ingeniously utilizes the power of a dynamically re-sizing array, allowing for seamless expansion and contraction of elements.

  1. Search Operation
  2. Manipulation
  3. Behaviour
  4. Memory Overhead

Search Operation

The search operation in ArrayList exhibits superior speed in comparison to LinkedList. The get(int index) method of ArrayList performs exceptionally with a time complexity of O(1), indicating constant time retrieval of elements. In contrast, the LinkedList's search performance is O(n), denoting a linear time complexity.

The disparity in performance stems from the distinctive data structures employed by both classes. ArrayList utilizes an index-based data structure, granting it the capability of random access to elements. This advantageous feature enables direct retrieval of elements by their respective indexes, resulting in swift search operations.

On the other hand, LinkedList lacks the luxury of indexes, rendering it incapable of facilitating direct access to elements. To retrieve or access an element from the list, LinkedList must traverse the entire list sequentially. This process incurs a linear time complexity, as the search operation depends on traversing each node until the desired element is found.

Thus, the inherent dissimilarities in the underlying data structures contribute to the disparity in search performance between ArrayList and LinkedList.

Manipulation

Performing manipulations with ArrayList can be perceived as comparatively sluggish due to its reliance on an internal array structure. Whenever an element insertion or deletion is required in ArrayList, it may necessitate a time complexity of O(n). This is due to the inherent nature of arrays, which demands shifting of elements to accommodate the changes.

Conversely, the manipulation capabilities of LinkedList outshine those of ArrayList, primarily owing to its utilization of a doubly linked list. This ingenious design eliminates the need for laborious bit shifting operations within the memory. Consequently, when it comes to element insertion or deletion in LinkedList, an impressive time complexity of O(1) is achieved. This is because LinkedList efficiently capitalizes on its doubly linked structure, enabling swift modifications without the need for extensive element reorganization.


ArrayList Vs LinkedList in Java

In terms of complexity and structure, an ArrayList is considered a more straightforward data structure compared to a LinkedList. An ArrayList utilizes a single array of pointers, occupying contiguous memory locations. The recreation of an ArrayList is only necessary when the array exceeds its allocated size, simplifying its management process.

While, a LinkedList comprises a chain of nodes, with each node being separately allocated and possessing front and back pointers to adjacent nodes. The intricate nature of LinkedList arises from its node-based structure, which introduces additional complexity and memory allocations.

When considering performance, an ArrayList typically outperforms a LinkedList, particularly in scenarios where middle insertion, splicing, or deletion operations are not required. The efficiency of an ArrayList stems from various factors. Firstly, it necessitates fewer memory allocations, reducing overhead. Secondly, it exhibits superior locality of reference, a crucial aspect for processor caching. The consecutive memory locations of an ArrayList enable efficient data retrieval, benefiting from the processor's cache hierarchy.

Behaviour

ArrayList functions as a List by virtue of its implementation of the List interface, thereby encapsulating the essential behaviors and characteristics associated with lists. On the other hand, LinkedList excels not only as a List but also as a Queue due to its implementation of both the List and Queue interfaces, affording it the versatility to perform diverse operations.

By implementing the List interface, ArrayList inherits and upholds the fundamental functionalities expected from a list data structure. It offers efficient element retrieval, modification, and traversal, all while maintaining the order of elements. ArrayList provides the convenience of indexed access to elements, enabling random access and facilitating operations such as sorting, filtering, and searching with ease.

In the case of LinkedList, its implementation of both the List and Queue interfaces imparts a remarkable range of capabilities. As a List, LinkedList encompasses the core functionalities of a list data structure, mirroring the behavior of ArrayList in terms of element management and ordering. However, LinkedList's distinct advantage lies in its dual role as a Queue, which introduces the concept of a first-in-first-out (FIFO) data structure. By adhering to the Queue interface, LinkedList allows for efficient insertion of elements at the tail and removal of elements from the head, adhering to the principles of a queue.

Therefore, while ArrayList confidently assumes the responsibilities of a List, LinkedList demonstrates exceptional versatility by embodying the characteristics of both a List and a Queue, rendering it a valuable asset in scenarios that require queue-like operations.

Memory Overhead

The ArrayList data structure efficiently manages indexes and element data, enabling quick access to elements. On the other hand, the LinkedList data structure not only stores element data but also incorporates two pointers to maintain connectivity with neighboring nodes. Consequently, the LinkedList consumes a higher amount of memory in comparison.

By utilizing the ArrayList, programmers can benefit from its ability to maintain a sequential index-based structure, allowing for rapid retrieval of elements based on their positions. This is particularly advantageous when there is a need for frequent access or manipulation of elements within the collection.

In contrast, the LinkedList adopts a different approach, emphasizing connectivity between elements through the use of pointers. With each element carrying references to both the preceding and succeeding nodes, the LinkedList facilitates efficient insertion and deletion operations, especially when dealing with extensive modifications to the data structure.

However, due to the additional memory requirements associated with storing the pointers alongside the actual element data, the LinkedList incurs a relatively higher memory consumption when compared to the ArrayList. This increased overhead must be considered when memory efficiency is a critical factor in the design and implementation of a data structure.

ArrayList Implementation

import java.util.*; class TestClass { public static void main (String[] args) { // create an array list Object ArrayList aList = new ArrayList(); aList.add("Sunday"); //adding item aList.add("Monday"); aList.add("Tuesday"); Iterator ir=aList.iterator(); while(ir.hasNext()){ System.out.println(ir.next()); } }
Output
Sunday Monday Tuesday

LinkedList Implementation

import java.util.*; class TestClass { public static void main (String[] args) throws java.lang.Exception { //create a new linked list object LinkedList days = new LinkedList(); // add elements to the linked list days.add("Monday"); days.add("Tuesday"); days.add("Wednesday"); days.add("Thursday"); days.addLast("Friday"); //Display all the contents of the LinkedList Iterator < String > itr=days.iterator(); while(itr.hasNext()){ System.out.println(itr.next()); } /*Add First and Last Element in linked list*/ days.addFirst("Sunday"); days.addLast("Saturday"); System.out.println("After Addition: " + days); //Insert an element in linked list days.add(0, "Days in a Week"); //add start of linked list days.add(4,"Middle"); //add in the middle of linked list days.add(9, "End"); //add in the lst of linked list System.out.println("After Insertion: " + days); } }
Output
Monday Tuesday Wednesday Thursday Friday After Addition: [Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, Saturday] After Insertion: [Days in a Week, Sunday, Monday, Tuesday, Middle, Wednesday, Thursday, Friday, Saturday, End]