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<meta charset="utf-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
<meta name="description" content="Data Structures and Algorithms Crash Course with Animated Illustrations and Off-the-Shelf Code">
<meta name="description" content="Data structures and algorithms tutorial with animated illustrations and ready-to-run code">
<meta name="author" content="krahets">
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<span class="md-ellipsis">
Chapter 1. Encounter With Algorithms
Chapter 1. Encounter with Algorithms
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<span class="md-nav__icon md-icon"></span>
Chapter 1. Encounter With Algorithms
Chapter 1. Encounter with Algorithms
</label>
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<span class="md-ellipsis">
Chapter 4. Array and Linked List
Chapter 4. Arrays and Linked Lists
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Chapter 4. Array and Linked List
Chapter 4. Arrays and Linked Lists
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<span class="md-ellipsis">
4.4 Memory and Cache *
4.4 Random-Access Memory and Cache *
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<span class="md-ellipsis">
Chapter 5. Stack and Queue
Chapter 5. Stacks and Queues
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Chapter 5. Stack and Queue
Chapter 5. Stacks and Queues
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<span class="md-ellipsis">
5.3 Double-Ended Queue
5.3 Deque
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<span class="md-ellipsis">
Chapter 6. Hashing
Chapter 6. Hash Table
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<span class="md-nav__icon md-icon"></span>
Chapter 6. Hashing
Chapter 6. Hash Table
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<span class="md-ellipsis">
7.3 Array Representation of Tree
7.3 Array Representation of Binary Trees
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<span class="md-ellipsis">
8.2 Building a Heap
8.2 Heap Construction Operation
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<span class="md-ellipsis">
8.3 Top-K Problem
8.3 Top-k Problem
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10.2 Binary Search Insertion
10.2 Binary Search Insertion Point
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10.3 Binary Search Edge Cases
10.3 Binary Search Boundaries
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10.5 Search Algorithms Revisited
10.5 Searching Algorithms Revisited
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<span class="md-ellipsis">
11.1 Sorting Algorithms
11.1 Sorting Algorithm
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<span class="md-ellipsis">
12.4 Hanoi Tower Problem
12.4 Hanota Problem
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16.3 Terminology Table
16.3 Glossary
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<h3 id="1-key-review">1. &nbsp; Key Review<a class="headerlink" href="#1-key-review" title="Permanent link">&para;</a></h3>
<ul>
<li>A stack is a data structure that follows the LIFO principle and can be implemented using arrays or linked lists.</li>
<li>In terms of time efficiency, the array implementation of a stack has higher average efficiency, but during expansion, the time complexity of a single push operation degrades to <span class="arithmatex">\(O(n)\)</span>. In contrast, the linked list implementation of a stack provides more stable efficiency performance.</li>
<li>In terms of time efficiency, the array implementation of a stack has higher average efficiency, but during expansion, the time complexity of a single push operation degrades to <span class="arithmatex">\(O(n)\)</span>. In contrast, the linked-list implementation of a stack offers more stable performance.</li>
<li>In terms of space efficiency, the array implementation of a stack may lead to some degree of space wastage. However, it should be noted that the memory space occupied by linked list nodes is larger than that of array elements.</li>
<li>A queue is a data structure that follows the FIFO principle and can also be implemented using arrays or linked lists. The conclusions regarding time efficiency and space efficiency comparisons for queues are similar to those for stacks mentioned above.</li>
<li>A deque is a queue with greater flexibility that allows adding and removing elements at both ends.</li>
</ul>
<h3 id="2-q-a">2. &nbsp; Q &amp; A<a class="headerlink" href="#2-q-a" title="Permanent link">&para;</a></h3>
<p><strong>Q</strong>: Is the browser's forward and backward functionality implemented with a doubly linked list?</p>
<p>The forward and backward functionality of a browser is essentially a manifestation of a "stack." When a user visits a new page, that page is added to the top of the stack; when the user clicks the back button, that page is popped from the top of the stack. Using a deque can conveniently implement some additional operations, as mentioned in the "Deque" section.</p>
<p>The browser's forward and backward behavior is essentially an application of a "stack." When a user visits a new page, that page is added to the top of the stack; when the user clicks the back button, that page is popped from the top of the stack. A deque can conveniently support some additional operations, as mentioned in the "Deque" section.</p>
<p><strong>Q</strong>: After popping from the stack, do we need to free the memory of the popped node?</p>
<p>If the popped node will still be needed later, then memory does not need to be freed. If it won't be used afterward, languages like Java and Python have automatic garbage collection, so manual memory deallocation is not required; in C and C++, manual memory deallocation is necessary.</p>
<p><strong>Q</strong>: A deque seems like two stacks joined together. What is its purpose?</p>
<p>A deque is like a combination of a stack and a queue, or two stacks joined together. It exhibits the logic of both stack and queue, so it can implement all applications of stacks and queues, and is more flexible.</p>
<p>A deque is like a combination of a stack and a queue, or two stacks joined together. It combines the logic of both, so it can support all applications of stacks and queues while offering greater flexibility.</p>
<p><strong>Q</strong>: How are undo and redo specifically implemented?</p>
<p>Use two stacks: stack <code>A</code> for undo and stack <code>B</code> for redo.</p>
<ol>
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<a
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aria-label="Previous: 5.3 Double-Ended Queue"
aria-label="Previous: 5.3 Deque"
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5.3 Double-Ended Queue
5.3 Deque
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</a>
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Next
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Chapter 6. &nbsp; Hashing
Chapter 6. &nbsp; Hash Table
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