Linked Lists - Swift Edition - Data Structures & Algorithms for AI-Era Interviews - Flannan P. Brody

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Autor: Flannan P. Brody

Editorial: Learn Algorithms Visually

Año: 12/10/2026

ISBN: 9798182899765

Encuadernación: Tapa blanda

Páginas: 228 pp.

Idioma: eng

EAN: 9798182899765


Stop memorizing pointer tricks. Start seeing why they work.
Linked Lists - Swift Edition teaches 56 linked-list algorithms through plain-language explanations, Swift implementations, and step-by-step visual walkthroughs that trace the structure through every pointer update. Every algorithm is shown in full color, so nodes, pointers, and changing links stand apart at a glance and are easy to trace.
Watch a list reverse one link at a time. Follow fast and slow pointers until they meet inside a cycle. See two sorted lists merge into one, and track the carry as two numbers are added digit by digit. Instead of holding every pointer in your head, follow the execution on the page.
The visual walkthroughs use small multiples, a data visualization technique that presents successive stages of an algorithm as a series of consistently structured diagrams. By seeing meaningful stages together, you can compare states, follow what moves, and understand how each decision affects the next. This brings the algorithm to life, reinforcing understanding and helping the underlying patterns and mechanics stay with you longer.
Every main algorithm is presented in three complementary parts:
Understanding & Reasoning: Learn the goal, key idea, edge cases, and time and space complexity before studying the implementation.
Inspect & Debug: Examine Swift code alongside an AI-Era Interview Lens that challenges you to question assumptions, recognize plausible mistakes, and explain why a solution is correct.
Trace & Walkthrough: Follow the input through intermediate states to the result, with visual explanations of the decisions that matter.
Part One builds the foundations - traversal, insertion, cycle detection, merging, and linked-list arithmetic. Part Two modernizes them for the AI era, reframing the same patterns around the judgement calls, verification habits, and debugging instincts that today?s interviews actually test.
In the AI era, DSA interviews are shifting from pure recall to judgement, verification, debugging, and exploration.
Every code sample was compiled, tested against edge cases beyond what?s printed on the page, and independently reviewed before making it into the book.
Designed for readers with basic Swift knowledge who want to strengthen coding interview preparation, debugging, and algorithmic reasoning.
Understand the idea. Follow the state. Explain the result.
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