LinkedList: A dynamic and flexible data structure in object-oriented mode

[Numeric1]

 Leveraging LinkedList for Efficient Data Management

 In the development of robust software solutions, the choice of data structure plays a pivotal role in achieving optimal performance and scalability. LinkedList, a dynamic data structure, offers unparalleled flexibility and efficiency in managing collections of data elements. Let's explore how LinkedList enhances the performance and flexibility of our codebase.

Efficient Memory Management: LinkedList excels in memory management by dynamically allocating memory for each element at runtime. Unlike static arrays, LinkedList adapts dynamically to accommodate varying numbers of elements, minimizing memory wastage and optimizing resource utilization.

Dynamic Insertion and Deletion: One of the key advantages of LinkedList is its ability to efficiently insert and delete elements from anywhere within the list. This dynamic nature enables seamless updates to the snake's body segments and food objects in our application, enhancing its responsiveness and fluidity.

Constant-Time Insertions and Deletions: LinkedList offers constant-time insertion and deletion operations, irrespective of the list size. This attribute is particularly advantageous in scenarios where frequent modifications to the data structure are required, such as adding new segments to the snake or removing consumed food items.

Iterative Traversal: LinkedList supports efficient traversal through its elements using iterators. This iterative access facilitates smooth navigation through the snake's body segments and food objects, enabling rapid processing of game logic and rendering updates.

Flexibility in Data Representation: LinkedList accommodates heterogeneous data types within the same list, allowing for versatile data representation. In our application, this flexibility enables us to store and manage diverse objects, such as snake segments and food items, within a single data structure seamlessly.

Conclusion: In summary, LinkedList emerges as a cornerstone of efficient data management in our application, providing dynamic memory allocation, constant-time insertions and deletions, and versatile data representation capabilities. By leveraging LinkedList, we optimize performance, enhance scalability, and lay a solid foundation for the seamless execution of our codebase.

 

 

The UDF has just been updated: Its performance has been optimized.

 

 

LinkedList.au3

Edited April 22 by Numeric1

[Danyfirex]

Add some samples to the UDF. 

 

Saludos

[Numeric1]

I'll give you examples of use. NB: the names of the functions you call do not include an underscord(_). For example for sorting you must call :  $myLinkedList.sort() and not $myLinkedList._sort()

1. Creating a Linked List and Inserting Elements:

$myList = LinkedList() ; Create a new linked list
$myList.insertAtEnd("A") ; Insert "A" at the end of the list
$myList.insertAtEnd("B") ; Insert "B" at the end of the list
$myList.insertAtEnd("C") ; Insert "C" at the end of the list

; Print the elements of the linked list
$myList.printLL() ; Output: A, B, C

2.Inserting at the Beginning:

$myList.insertAtBegin("X") ; Insert "X" at the beginning of the list

; Print the elements of the linked list
$myList.printLL() ; Output: X, A, B, C

 

3.Inserting at a Specific Index:

$myList.insertAtIndex("Y", 2) ; Insert "Y" at index 2 (0-based)

; Print the elements of the linked list
$myList.printLL() ; Output: X, A, Y, B, C

 

4. Updating a Node at a Specific Index:

$myList.updateNode("Z", 1) ; Update the element at index 1 to "Z"

; Print the elements of the linked list
$myList.printLL() ; Output: X, Z, Y, B, C

 

5. Removing Elements:

$myList.remove_first_node() ; Remove the first element
$myList.remove_last_node() ; Remove the last element
$myList.remove_at_index(1) ; Remove the element at index 1

; Print the elements of the linked list
$myList.printLL() ; Output: Z, B

 

6. Searching for an Element:

$position = $myList.search("B") ; Search for "B"

If $position <> -1 Then
    ConsoleWrite("Found at index " & $position & @CRLF)
Else
    ConsoleWrite("Not found" & @CRLF)
EndIf

7. Reversing the Linked List:

 

$myList.reverse() ; Reverse the linked list

; Print the reversed linked list
$myList.printLL() ; Output: B, Z

 

8. Iterating Over the Linked List:

$iterator = $myList.iterator()

While Not $iterator.isDone()
    $data = $iterator.next()
    ConsoleWrite("Element: " & $data & @CRLF)
WEnd

 

A singly linked list data structure has specific performance characteristics in terms of execution time for various operations. Here is an explanation of the performance for each common operation on a singly linked list:

1. Insertion at the Head (adding an element at the beginning):
   - Performance: O(1)
   - Explanation: Inserting at the head of a singly linked list is highly efficient because it only requires modifying a pointer (the head) to point to the new node. There is no need to traverse the entire list.

2. Insertion at the End (appending an element to the end):
   - Performance: O(n), where n is the number of elements in the list
   - Explanation: To insert an element at the end, you need to traverse the entire list to reach the last node for the insertion.

3. Insertion at a Specific Index:
   - Performance: O(n), where n is the insertion index
   - Explanation: To insert an element at a specific index, you need to traverse the list up to that index to perform the insertion. In the worst case, this may require traversing the entire list.

4. Deletion at the Head (removing the first element):
   - Performance: O(1)
   - Explanation: Deletion at the head is an efficient operation because it involves simply modifying the head pointer to exclude the first node.

5. Deletion at the End (removing the last element):
   - Performance: O(n), where n is the number of elements in the list
   - Explanation: To delete the last element, you need to traverse the entire list to reach the second-to-last node and then modify its "Next" pointer to exclude the last element.

6. Deletion at a Specific Index:
   - Performance: O(n), where n is the deletion index
   - Explanation: To delete an element at a specific index, you need to traverse the list up to that index to perform the deletion. In the worst case, this may require traversing the entire list.

7. Search for an Element by Value:
   - Performance: O(n), where n is the number of elements in the list
   - Explanation: To search for an element by value, you need to traverse the list from the beginning until you find the desired element. In the worst case, this may require traversing the entire list.

8. Reversing the List:
   - Performance: O(n), where n is the number of elements in the list
   - Explanation: Reversing the list requires traversing all the elements in the list to reverse the "Next" pointers of the nodes.

Singly linked lists generally have good performance for head insertion, head deletion, and element access operations. However, operations such as search, tail insertion, tail deletion, and insertion/deletion at a specific index can be less efficient due to the need to traverse the list. For frequent operations involving searching or accessing elements by index, other data structures like arrays may be more efficient.