In Java, LinkedList is a part of the Java Collections Framework and implements both the List and Deque interfaces. It is a doubly-linked list, where each element (node) contains references to both the next and previous nodes. This structure makes it well-suited for scenarios where you frequently insert or delete elements from the beginning or middle of the list.

LinkedList in Java is ideal for scenarios where frequent insertions and deletions are needed, especially at the start or middle of the list. It provides O(1) insertion and deletion for these operations, unlike ArrayList which requires O(n) due to shifting. However, it sacrifices performance when it comes to random access and searching since these operations take O(n) due to the need for traversal.

If you need fast access by index or are working with a large dataset where random access is important, ArrayList may be a better choice. On the other hand, if your use case involves many insertions or deletions and sequential access, LinkedList is a better fit.

Advantages #

1. Efficient Insertions/Deletions: Insertions and deletions at the beginning or in the middle of the list are more efficient (O(1)) compared to ArrayList, which requires shifting elements (O(n)).
2. No Resizing Cost: Unlike ArrayList, a LinkedList doesn’t need to resize itself since its elements are linked using pointers, allowing dynamic growth without reallocation.
3. Flexibility: It can act as both a List and a Deque (double-ended queue), making it suitable for implementing stacks, queues, or deques.
4. Bi-Directional Navigation: Since it’s a doubly linked list, it allows traversing in both forward and backward directions efficiently.

Disadvantages #

1. Memory Overhead: Each node in a LinkedList stores a reference to both the next and previous nodes, consuming more memory compared to ArrayList, which uses a contiguous block of memory.
2. Slow Random Access: Unlike ArrayList, accessing an element by index takes O(n) time because you need to traverse the list from the beginning or end to the desired index.
3. Less Cache-Friendly: Elements in a LinkedList are scattered across memory rather than being stored contiguously like in an array, so it does not benefit from CPU cache locality as ArrayList does.

Time and Space Complexity #

Examples #

1. Initialization and Adding Elements:

   • Time Complexity: O(1) (for adding to the start/end)

   // Initialize a LinkedList
   LinkedList<Integer> list = new LinkedList<>();
   
   // Add elements to the list
   list.add(1);  // [1]
   list.add(2);  // [1, 2]
   list.addFirst(0);  // [0, 1, 2]
   list.addLast(3);  // [0, 1, 2, 3]
   

2. Accessing Elements by Index:

   • Time Complexity: O(n)

   // Access an element by index (traverses the list)
   int element = list.get(2);  // Returns 2 (the element at index 2)
   

3. Inserting at a Specific Index:

   • Time Complexity: O(n) (due to traversal)

   // Insert element at index 1
   list.add(1, 10);  // [0, 10, 1, 2, 3]
   

4. Removing an Element:

   • Time Complexity: O(1) for removing the first/last element, O(n) for removing by index

   // Remove the first element
   list.removeFirst();  // [10, 1, 2, 3]
   
   // Remove an element by index
   list.remove(1);  // [10, 2, 3] (removes element at index 1)
   

5. Iterating Over a LinkedList:

   • Time Complexity: O(n)

   // Iterate over the LinkedList
   for (Integer num : list) {
       System.out.println(num);
   }
   

6. Using LinkedList as a Queue/Deque:

   • Time Complexity: O(1) for adding/removing at the beginning/end

   // Queue behavior: Add elements at the end, remove from the front
   LinkedList<Integer> queue = new LinkedList<>();
   queue.addLast(1);  // Enqueue
   queue.addLast(2);
   int dequeued = queue.removeFirst();  // Dequeue (returns 1)
   
   // Stack behavior: Add and remove from the same end (LIFO)
   LinkedList<Integer> stack = new LinkedList<>();
   stack.push(1);  // Push
   stack.push(2);
   int popped = stack.pop();  // Pop (returns 2)
   

7. Searching for an Element:

   • Time Complexity: O(n)

   boolean exists = list.contains(10);  // Returns true if 10 exists in the list