DSA Basics Sheet
The DSA Basics sheet is an ordered first pass through data structures and algorithms: each lesson introduces one structure or technique, explains when it applies, and hands you an executable problem that cannot be solved without it.
The sheet holds 12 patterns and 76 topics, tracked row by row. From any row you can read the theory for a topic, solve the mapped problem in the browser, sit a mock interview on it, have the AI coach teach it back to you, keep notes, bookmark a row and mark it done. Progress is saved against your account, so the sheet is also the record of what you have already covered.
Who it is for
It is written for someone who can write a loop and a function but has never implemented a hash map, a heap or a graph traversal by hand. If you already recognise the pattern behind a question and only need volume, start from the DSA Patterns sheet instead.
How to work through it
Work top to bottom rather than by difficulty. The order is a dependency order — complexity before recursion, recursion before trees, trees before graphs — so a lesson you skip resurfaces as the reason a later one will not click. Write the code before reading the solution, then compare.
Practice runs on the same platform as the sheet: 850+ problems across every track, code execution in 6 languages, and AI mock interviews that follow the pattern you are studying rather than a random question.
What the dsa basics sheet covers
Data Structures and Algorithms Foundations
12 topics in dependency order, from complexity through graph traversal
- Foundations of Complexity — Time Complexity Concepts, Space Complexity Concepts, Asymptotic Notations, Common Complexity Classes, Loop Analysis, Performance Case Analysis
- Arrays & Memory Layout — Array Memory Allocation, Indexing and Traversal, Insertion & Deletion in Arrays, Prefix and Suffix Techniques, Sliding Window Basics, Array Reversal and Rotation
- Number Theory & Arithmetic — Divisibility Logic, Prime Numbers & Factorization, GCD and LCM, Modular Arithmetic, Binary Representation & Bit Tricks, Fast Exponentiation
- Strings & Pattern Formation — String Representation, Character Arrays vs Immutable Strings, String Manipulation Operations, Substring and Pattern Matching, Frequency Counting in Strings, Two-pointer Techniques
- Basic Linked Lists — Node Structure and Pointers, Traversal in Linked Lists, Insertion Techniques, Deletion Techniques, Dummy and Sentinel Nodes, Circular Linked List Concepts
- Stacks and Queues — Stack Operations, Queue Operations, Implementation Approaches, Circular Queue Mechanics, Expression Parsing Basics, Monotonic Stack and Queue
- Hashing Fundamentals — Direct Addressing vs Hash Table, Hash Functions, Collision Handling - Chaining, Collision Handling - Open Addressing, Load Factor and Rehashing, Frequency Maps and Sets
- Recursion Essentials — Recursive Function Design, Base and Recursive Case, Recursion Tree Analysis, Tail Recursion, Recursive Traversal of Arrays and Strings, Memoization Introduction
- Elementary Sorting — Sorting Contracts and Properties, Bubble Sort, Selection Sort, Insertion Sort, Merging Sorted Runs, Merge Sort, Partitioning Around a Pivot, Quick Sort, Heapify and Heap Sort, Counting, Radix and Bucket Sorting
- Searching Strategies — Linear Search, Binary Search Fundamentals, Binary Search Variants, Search in Rotated Arrays, Search Space Reduction, Ternary Search Basics
- Binary Tree Basics — Tree Terminology and Structure, Binary Tree Properties, Tree Representation Techniques, DFS Traversals, BFS Traversal, Height and Size Calculation
- Graphs Basics — Graph Terminology and Types, Adjacency List and Matrix, Breadth First Search, Depth First Search, Connected Components, Intro to Weighted Graphs
