92 lines
4.1 KiB
Markdown
Executable File
92 lines
4.1 KiB
Markdown
Executable File
# The Abstract Data Type: Linear List
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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.
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## Implementing ADT Linear List
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The Linear List can be implemented using different structures, including linked lists. The main focus here is on:
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- Linear List based on LinkedList
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- Doubly-linked list
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Each of these implementations has its unique characteristics, advantages, and considerations.
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## Sizes of Primitive Data Types
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Understanding the size of primitive types is fundamental in memory allocation:
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- **boolean & byte** - 1 byte
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- **char & short** - 2 bytes
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- **int & float** - 4 bytes
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- **long & double** - 8 bytes
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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.
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## Linked List vs. Array List
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When comparing Array Lists and Linked Lists:
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- **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.
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- **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.
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## Memory Allocation Concepts
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Memory allocation for both primitive types and objects follows specific rules:
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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.
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## Understanding Linked Lists
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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.
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### Operations on Linked Lists
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Some common operations performed on linked lists include:
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- **Insertion**: Nodes may be inserted at the beginning, middle, or end of the list, requiring adjustments of pointers accordingly.
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- **Removal**: Similar to insertion, removal requires accessing the right node and adjusting pointers to maintain list integrity.
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### Algorithm Visualizations
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Visual representations can help understand operations such as inserting or deleting nodes. For example, to insert a node in a linked list, one must:
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1. Create the new node.
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2. Adjust the pointers of the surrounding nodes to include the new node.
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## Doubly-Linked Lists
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Doubly-linked lists add an extra pointer, allowing traversal in both forward and backward directions, enhancing flexibility:
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- **Advantages**: They can traverse in both directions and manage dynamic memory more efficiently.
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- **Disadvantages**: They require more memory for pointers and tend to have slower access times due to their random memory allocation.
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### Inserting and Deleting in Doubly-Linked Lists
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The process of inserting or deleting nodes involves managing the **prev** and **next** pointers to maintain the structure of the list. As illustrated:
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1. For insertion, properly link the new node with its neighbors.
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2. For deletion, ensure that surrounding nodes bypass the removed node, effectively maintaining list integrity.
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## Key Takeaways
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In conclusion, choosing between an array and a linked list largely depends on the intended operations:
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- **Arrays** are optimal for scenarios where quick search operations are prioritized.
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- **Linked Lists** are preferred for scenarios where insertion and deletion operations are frequent, with variations including:
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- **Singly Linked List**: Best suited for simple sequential access and minimal memory overhead.
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- **Doubly Linked List**: Ideal when navigating both forwards and backwards is necessary.
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Understanding these structures and their operations is essential for effective programming and data management.
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