Algorithm Design Patterns

Two Pointers, Sliding Window, BFS/DFS, and DP Templates — A TLDR Primer

Most students hit a wall with algorithms — not because the problems are impossible, but because no one showed them the underlying patterns. Once you see that dozens of array and string problems reduce to the same sliding window or two-pointer template, the whole subject clicks into place.

**TLDR: Algorithm Design Patterns** is a focused, short-by-design guide covering the handful of techniques that appear on coding exams, intro CS assignments, and technical interviews again and again: two pointers, sliding window, binary search and divide & conquer, graph traversal (BFS and DFS), and dynamic programming. Each section gives you a clean, reusable template, explains exactly when to reach for it, and walks through worked examples with real code-style logic you can adapt on the spot.

This book is written for high school students in AP Computer Science or competitive programming, college freshmen and sophomores taking their first algorithms course, and self-taught coders preparing for technical interviews who need a quick reference for coding interview patterns without wading through a 600-page textbook.

It is deliberately concise. You can read it in a single study session, then return to individual sections right before a problem set or exam. Every section leads with the one thing you need to remember, corrects the misconceptions that trip students up most, and closes with a pattern-matching checklist so you can identify which technique a new problem is asking for.

If algorithm design patterns for beginners have ever felt like magic tricks other people know — this primer hands you the trick.

What you'll learn

Recognize when a problem fits a known pattern (sliding window, two pointers, binary search, BFS/DFS, dynamic programming) instead of solving from scratch.
Write and adapt clean code templates for each pattern in a language-agnostic way.
Reason about time and space complexity well enough to choose between competing approaches.
Avoid the most common pitfalls (off-by-one errors, wrong loop invariants, missing base cases) that trip students on exams and interviews.

What's inside

1. What Is an Algorithm Design Pattern?

Orients the reader: a pattern is a reusable problem-solving template, not a specific algorithm, and learning a small set covers most problems you'll see.
2. Two Pointers

Covers the two-pointers pattern on sorted arrays and strings, including opposite-end and same-direction variants, with worked examples like pair sum and palindrome checks.
3. Sliding Window

Explains fixed-size and variable-size sliding windows for substring and subarray problems, with templates for 'longest/shortest window satisfying condition'.
4. Binary Search and Divide & Conquer

Covers binary search beyond sorted arrays — searching the answer space — plus the divide-and-conquer template behind merge sort and similar algorithms.
5. Graph Traversal: BFS and DFS

Presents breadth-first and depth-first search as the universal traversal patterns, with templates for grids, trees, and explicit graphs, plus when to pick which.
6. Dynamic Programming and Pattern Recognition

Introduces DP as 'recursion plus memory,' shows the standard 1D and 2D templates, and closes with a checklist for matching any new problem to one of the patterns in this book.

Published by Solid State Press

TLDR STUDY GUIDES

Algorithm Design Patterns

Two Pointers, Sliding Window, BFS/DFS, and DP Templates — A TLDR Primer

Solid State Press

Algorithm Design Patterns

Two Pointers, Sliding Window, BFS/DFS, and DP Templates — A TLDR Primer

Published by Solid State Press.

Part of the TLDR Study Guides series.

1 What Is an Algorithm Design Pattern?
2 Two Pointers
3 Sliding Window
4 Binary Search and Divide & Conquer
5 Graph Traversal: BFS and DFS
6 Dynamic Programming and Pattern Recognition

Chapter 1

What Is an Algorithm Design Pattern?

Think about the last time you faced a math problem you had never seen before and suddenly recognized it as a disguised version of something you already knew how to do. That flash of recognition — "this is just a rate problem" or "this is just a proportion" — is worth more than memorizing any single formula. The same thing happens in computer science, and algorithm design patterns are the framework that makes it happen systematically.

An algorithm is a precise, step-by-step procedure for solving a problem. An algorithm design pattern is one level more abstract than that: it is a reusable template for a class of problems. Where a specific algorithm solves one problem (binary search finds a target in a sorted array), a pattern gives you a shape you can adapt to dozens of different problems. Learning the pattern means you are not starting from a blank page each time — you are recognizing a familiar structure and filling in the details.

This distinction matters because the space of possible programming problems is enormous, but the space of useful patterns is small. Research on competitive programming and technical interviews consistently finds that a handful of patterns — two pointers, sliding window, binary search, graph traversal, dynamic programming — covers the majority of problems you will encounter in introductory courses and coding interviews. This book covers exactly those patterns.

What a template looks like

A template is a partial piece of code (or pseudocode) with clearly labeled blanks you fill in for each specific problem. It encodes the invariant — the condition that stays true throughout the algorithm's execution — so you do not have to rediscover it each time. Here is a deliberately vague example to illustrate the idea:

initialize pointers or boundaries
while stopping condition is not met:
    check or update the current state   ← you fill this in
    advance one or both pointers        ← you fill this in
return the answer

About This Book

If you're taking an intro CS algorithms course in high school or college, prepping for AP Computer Science, or staring down your first technical interview, this book was written for you. It's also a solid resource for self-taught programmers who keep hearing about patterns like sliding window and two pointers but want them explained simply, without jargon or hand-waving.

This is a coding interview patterns study guide and a classroom primer in one. It covers algorithm design patterns for beginners — two pointers, sliding window, binary search, divide and conquer, graph traversal with BFS and DFS, and a dynamic programming primer — each with templates you can adapt on the spot. A concise overview with no filler.

Read straight through once to build the mental map, then work every example as you go — don't just read the solution. At the end, a short problem set lets you confirm you can apply each pattern cold, which is exactly what an exam or interview requires.

Keep reading

You've read the first half of Chapter 1. The complete book covers 6 chapters in roughly fifteen pages — readable in one sitting.

Coming soon to Amazon