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Graphs & Greedy - Java Edition
Data Structures & Algorithms for AI-Era Interviews
This book is 100% completeLast updated on 2026-10-20
Graphs & Greedy - Java Edition teaches 49 graph and greedy algorithms through plain-language explanations, Java implementations, and step-by-step visual walkthroughs that trace every visited node, relaxed edge, and... Printed in full color.
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About
About the Book
Stop memorizing graph algorithms. Start seeing why they work.
Graphs & Greedy - Java Edition teaches 49 graph and greedy algorithms through plain-language explanations, Java implementations, and step-by-step visual walkthroughs that trace every visited node, relaxed edge, and greedy choice. Every algorithm is shown in full color, so visited nodes, frontiers, and changing distances stand apart at a glance and are easy to trace.
Watch breadth-first search expand level by level. Follow Dijkstra as it relaxes one edge at a time. See union-find merge components and a spanning tree grow edge by edge. Instead of holding every intermediate step 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 Java 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.
The eight pattern families cover Greedy Foundations, Graph Foundations, BFS Puzzles, Topological Sort, Shortest Paths, Union-Find & Minimum Spanning Trees, Connectivity, and Flow & Matching. From activity selection and Huffman coding to Dijkstra, Kruskal, Tarjan, and Edmonds-Karp, each pattern builds on the one before it.
A graph looks like a picture until you have to walk it, and a greedy choice looks obvious until it quietly fails. This book is about knowing which edge to take next, and proving why it is the right one.
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 Java knowledge who want to strengthen coding interview preparation, debugging, and algorithmic reasoning.
Understand the idea. Follow the state. Explain the result.
Author
About the Author
Flannan P. Brody
Flannan P. Brody is a software engineer with over 18 years of experience building large-scale systems at companies including Google, Apple, Disney+, and Genentech. A graduate of the Dublin Institute of Technology, he has navigated the high-stakes technical interview loops of the world's most selective tech companies more times than he'd care to admit.
Learn Algorithms Visually was born directly from those repeated cycles. Every return trip to the interview circuit brought a deeper layer of clarity, stripping away academic abstraction to reveal how algorithms actually function under the hood. This series is his attempt to compress years of hard-won insight into a single, intuitive pass.
When he isn't writing or architecting code, he's usually playing soccer or traveling.
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