Learn Linked Lists in 13 minutes 🔗
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- Опубліковано 8 вер 2024
- LinkedList data structures and algorithms tutorial example explained
#linkedlist #linkedlists #tutorial
// *******************************************************
// LinkedList = Nodes are in 2 parts (data + address)
// Nodes are in non-consecutive memory locations
// Elements are linked using pointers
// advantages?
// 1. Dynamic Data Structure (allocates needed memory while running)
// 2. Insertion and Deletion of Nodes is easy. O(1)
// 3. No/Low memory waste
// disadvantages?
// 1. Greater memory usage (additional pointer)
// 2. No random access of elements (no index [i])
// 3. Accessing/searching elements is more time consuming. O(n)
// uses?
// 1. implement Stacks/Queues
// 2. GPS navigation
// 3. music playlist
// *******************************************************
TL;DR
small data set: LinkedList = BAD
large data set + lots of searching: LinkedList = BAD
large data set + lots of inserting/deleting: LinkedList = GOOD
import java.util.LinkedList;
public class Main{
public static void main(String[] args) {
// *******************************************************
// LinkedList = Nodes are in 2 parts (data + address)
// Nodes are in non-consecutive memory locations
// Elements are linked using pointers
// advantages?
// 1. Dynamic Data Structure (allocates needed memory while running)
// 2. Insertion and Deletion of Nodes is easy. O(1)
// 3. No/Low memory waste
// disadvantages?
// 1. Greater memory usage (additional pointer)
// 2. No random access of elements (no index [i])
// 3. Accessing/searching elements is more time consuming. O(n)
// uses?
// 1. implement Stacks/Queues
// 2. GPS navigation
// 3. music playlist
//
// *******************************************************
LinkedList linkedList = new LinkedList();
/*
// LinkedList as a Stack
linkedList.push("A");
linkedList.push("B");
linkedList.push("C");
linkedList.push("D");
linkedList.push("F");
linkedList.pop();
*/
// LinkedList as a Queue
linkedList.offer("A");
linkedList.offer("B");
linkedList.offer("C");
linkedList.offer("D");
linkedList.offer("F");
//linkedList.poll();
//linkedList.add(4, "E");
//linkedList.remove("E");
//System.out.println(linkedList.indexOf("F"));
//System.out.println(linkedList.peekFirst());
//System.out.println(linkedList.peekLast());
//linkedList.addFirst("0");
//linkedList.addLast("G");
//String first = linkedList.removeFirst();
//String last = linkedList.removeLast();
System.out.println(linkedList);
}
}
🌹🌹🌹
may i know why 1. implement Stacks/Queues
// 2. GPS navigation
// 3. music playlist
is more suitable to use linked list?
😅
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Hey, Bro! Could you (or any other of you folks grasping big Oh notation) explain, why inserting and deleting is O(1) and not O(n)? Would'nt the algorithm need to traverse the nodes to find the appropriate place to change the addresses for the newly created element?
I'm still learning, but i've also been thinking about this, and i think you're right. The time complexity of O(1) for deleting and adding data in a linked list is only at the beginning and end of the list, because there is no need to shift elements like in an array. However, the time complexity becomes linear, O(n), if the element is somewhere "inside" the list. Because linked lists do not have indexes (that's the whole point), the element you want to delete or change within a list has to be found first, and as i understand, it is done by traversing the list. You have to go through all the elements of the list until the end or until a matching element is found.
So the main advantage of linked lists over arrays is that they can shrink and grow faster if elements are added or deleted from the beginning or end of a list.
@@NikolasToCorealso learning but I think deleting at end is O(n) not O(1) since you need to transverse through the whole thing to know where the new end is. Deleting at the beginning is definitely O(1) though
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Random comment is comment
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how can we create singly linked lists?
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