CLRS.Helper[Lite] vs Data Structures and Algorithms

Refer to The third edition of the book, covering content [need full version]: 2. Getting Started: Insertion sort, Merge sort; 4. Divide-and-Conquer: Maximum-subarray, Matrix Multiplication[normal, recursive, Strassen’s algorithm]; 6. Heapsort: Heapsort[max-heap, min-heap]; 7. Quicksort: Quicksort; 8. Sorting in Linear Time: Counting sort; 12. Binary Search Trees: Binary search tree[Inorder Walk, Search Recursive, Search Iterative, Minimum Iterative, Maximum Iterative, Successor, Predecessor, Insert, Delete]; 13. Red-Black Trees: Red Black Tree[Insert, Delete]; 15. Dynamic Programming: Rod cutting[Recursive, Top_down, Bottom_up, Print],Longest common subsequence; 16. Greedy Algorithms: Acitivity selection[Recursive, Iterative],Huffman codes; 22. Elementary Graph: Breadth-first search, Depth-first search, Topological sort, Strongly connected components; 23. Minimum Spanning Trees: Minimum spanning tree[Kruskal’s algorithm，Prim’s algorithm]; 24. Single-Source Shortest Paths: The Bellman-Ford algorithm，DAG algorithm，Dijkstra’s algorithm; 25. All-pairs Shortest Paths: All-pairs Shortest paths algorithms[Slow，Faster，The Floyd-Warshall algorithm]; 26. Maximum Flow: The Ford-Fulkerson algorithm; Addition: Tower of Hanoi，N Queens Problem，Comparison of sorting algorithms; The primary features: You can run the pseudo-code single step or continuous, observe the change of parameters and data structures，it can help you to understand the design thought of the algorithm; You can set breakpoints in program and ovserve the status of breakpoint, it can help you to understand why this algorithm is corrcet by using loop invariants; With running-time function stacks and the returning positions，you can track the running process of recursive functions easily, and understand the operation mechanism of computer programs; By recording the performed times of the pseudo-codes can help you to understand the running time of algorithms; I wish this app can be helpful to you;

DSA is a visual learning app for computer science students, exam prep, and self-learners. Turn abstract data structure concepts into step-by-step animations so you can actually see how algorithms work. WHY DSA • Dual-mode learning: read concept lessons first, then run interactive step-by-step visualizers • Smooth animations: pointer moves, swaps, assignments, and tree restructuring are animated with clear step descriptions • Structured curriculum: organized by textbook chapters from fundamentals to advanced topics • Full playback control: previous/next step, auto-play, speed adjustment, and scrubbing • Multilingual: Simplified Chinese, English, and more COURSE CONTENT Ch. 1 Introduction Asymptotic notation, simplification rules, time & space complexity with examples Ch. 2 Linear Lists, Stacks & Queues Linear lists, stack operations & applications, queue operations & circular queues Ch. 3 Arrays & Matrices Array basics, special matrix compression Ch. 4 Strings BF, KMP, BM string matching, algorithm complexity comparison Ch. 5 Trees Tree basics, binary tree properties & traversals BST, AVL, Splay, B-tree, Red-Black Tree, B+ Tree, Huffman Tree, Union-Find Ch. 6 Graphs Graph basics, storage structures, traversal Minimum spanning tree, shortest paths, topological sort & critical path Ch. 7 Sorting Bubble, Selection, Insertion, Shell, Merge, Quick, Heap Sort Counting, Bucket, Radix Sort Winner Tree, Loser Tree, complexity comparison WHO IT'S FOR • CS / Data Structures students • Exam prep and interview review • Self-learners building a solid DSA foundation FULL UNLOCK One-time purchase unlocks all content. No subscription. No ads. Restore purchases supported. Feedback: Settings → Email Feedback