CSE 326 · Algorithms · Spring 2025–2026

Analysis & Design
of Algorithms · Study Guide

Socratic walkthroughs & practice quizzes for the full course
قبل ما تبدا سمي الله و صلي عالنبي

Welcome 👋

This interactive study guide is designed to help you master Analysis and Design of Algorithms — from binary search and Big O all the way to Dijkstra, greedy strategies, and KNN. Navigate through different learning styles using the modes below:

  • 📖 Tutorial Mode: Walk through guided Socratic explanations, interactive code snippets, and review core lecture concepts step-by-step.
  • 🔧 Interactive Coding: Practice writing and arranging Python algorithm code with real-time check feedback.
  • ⚡ Practice Quiz: Challenge yourself with exam-style multiple-choice questions, detailed explanations, and track your mistakes.
  • ⚡🔧 Blitz Coding: Test your skills with customized, randomized coding tasks across multiple topics to build speed and accuracy.

💡 Pro-Tip: Press Ctrl+K (or click the search 🔍 icon next to Home) to search for anything instantly across tutorials, quizzes, and coding tasks. You can also view reference answers using the new 🔓 Solution button during coding tasks!

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Tutorial Mode
Learn with structured walkthroughs and interactive step-by-step hints
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Interactive Coding
Practice writing code with fill-in, line builder, and scratch coding
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Practice Quiz
Test your understanding with exam-style MCQs and track mistakes
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Blitz Coding
Practice randomized coding tasks across multiple topics with custom counts
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Practice modeShow the correct answer & explanation after each question
Shuffle questionsRandomize the order each attempt
Sheet questions only Restrict the pool to coding tasks pulled from the practice sheets
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Mix question stylesInterleave fill, line builder, and scratch coding questions
Shuffle questionsRandomize the order each attempt
TUTORIAL MODEChoose a topic
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🔍
Intro & Binary Search (Lecture 1)
What an algorithm is · data structures · linear vs binary search · logarithms · O(log n)
📊
Big O Notation (Lecture 2)
Worst-case analysis · the 5 common run times · O(log n) → O(n!) · travelling salesperson
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Arrays, Linked Lists & Selection Sort (Lecture 3)
Memory model · contiguous vs scattered · random vs sequential access · selection sort O(n²)
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Recursion (Lecture 4)
Base case vs recursive case · the call stack · LIFO push/pop · factorial · stack overflow
Quicksort & Divide and Conquer (Lecture 5)
D&C strategy · farm-plot GCD · partition around a pivot · O(n log n) avg, O(n²) worst
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Hash Tables (Lecture 6)
Hash functions · collisions · chaining · load factor & resize · DNS, caching, dedup
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Breadth-First Search (Lecture 7)
Graphs · BFS levels · queues (FIFO) · directed vs undirected · topological sort · O(V+E)
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Dijkstra's Algorithm (Lecture 8)
Weighted graphs · 4-step procedure · parent table · trading-for-piano · negative weights → Bellman-Ford
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Greedy Algorithms & NP (Lecture 9)
Greedy strategy · classroom scheduling · knapsack failure · set covering · P/NP/NP-hard/SAT
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K-Nearest Neighbors (Lecture 10)
Classification & regression · Euclidean distance · features · recommendations · OCR · Naive Bayes
LINKSMore Practice
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CODING MODEPick a topic
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FILL
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