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G4G0-2/Data Structures/AI Notes/Linear List.md
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The Abstract Data Type: Linear List

This study material provides a concise overview of the Abstract Data Type (ADT) known as the Linear List, focusing on its implementation using linked lists, particularly doubly-linked lists. Understanding these concepts is crucial for effectively managing data structures in programming.

Implementing ADT Linear List

The Linear List can be implemented using different structures, including linked lists. The main focus here is on:

  • Linear List based on LinkedList

  • Doubly-linked list

Each of these implementations has its unique characteristics, advantages, and considerations.

Sizes of Primitive Data Types

Understanding the size of primitive types is fundamental in memory allocation:

  • boolean & byte - 1 byte

  • char & short - 2 bytes

  • int & float - 4 bytes

  • long & double - 8 bytes

It's important to note that, in modern 64-bit Java Virtual Machines (JVM), the minimum size of an object is 16 bytes due to the header size and padding requirements.

Linked List vs. Array List

When comparing Array Lists and Linked Lists:

  • Addition and Removal: Linked Lists excel in scenarios where frequent addition and removal of elements are required due to their dynamic size and absence of resizing overhead.

  • Memory Overhead: Linked Lists consume more memory because each node contains a reference to both the next and, in doubly-linked lists, the previous node, which increases complexity and size.

Memory Allocation Concepts

Memory allocation for both primitive types and objects follows specific rules:

For instance, when assigning one variable to another: each variable allocated for an object points to the memory address where the object is stored. This is evidenced when variables such as smith and jones point to the same Account object, illustrating memory referencing in Java.

Understanding Linked Lists

A linked list is a collection of nodes where each node contains data and a reference (or pointer) to the next node, allowing for efficient insertion and deletion operations. Linked lists can store various types of information, making them versatile data structures.

Operations on Linked Lists

Some common operations performed on linked lists include:

  • Insertion: Nodes may be inserted at the beginning, middle, or end of the list, requiring adjustments of pointers accordingly.

  • Removal: Similar to insertion, removal requires accessing the right node and adjusting pointers to maintain list integrity.

Algorithm Visualizations

Visual representations can help understand operations such as inserting or deleting nodes. For example, to insert a node in a linked list, one must:

  1. Create the new node.

  2. Adjust the pointers of the surrounding nodes to include the new node.

Doubly-Linked Lists

Doubly-linked lists add an extra pointer, allowing traversal in both forward and backward directions, enhancing flexibility:

  • Advantages: They can traverse in both directions and manage dynamic memory more efficiently.

  • Disadvantages: They require more memory for pointers and tend to have slower access times due to their random memory allocation.

Inserting and Deleting in Doubly-Linked Lists

The process of inserting or deleting nodes involves managing the prev and next pointers to maintain the structure of the list. As illustrated:

  1. For insertion, properly link the new node with its neighbors.

  2. For deletion, ensure that surrounding nodes bypass the removed node, effectively maintaining list integrity.

Key Takeaways

In conclusion, choosing between an array and a linked list largely depends on the intended operations:

  • Arrays are optimal for scenarios where quick search operations are prioritized.

  • Linked Lists are preferred for scenarios where insertion and deletion operations are frequent, with variations including:

    • Singly Linked List: Best suited for simple sequential access and minimal memory overhead.

    • Doubly Linked List: Ideal when navigating both forwards and backwards is necessary.

Understanding these structures and their operations is essential for effective programming and data management.