CLRS.Helper[Lite] vs Data Structure Display Usage & Stats
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;
- Apple App Store
- Free
- Education
Store Rank
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A novel data structure learning app, the most significant feature is that you can dynamically debug the data structure in this app, and visually observe the changes in the data structure during the operation. In this app you can learn the following data structures:
1. Linear structures, including arrays, linked lists, queues, stacks. Linear structures are the basis for other advanced data structures, as fine as advanced algorithms.
2. Tree structures, including binary tree, binary search tree, AVL tree, red-black tree, and heap. In this app, you can dynamically debug three traversals of the binary tree (including non-recursive traversal implementations), searching in the tree, balance adjustments in the AVL tree and red-black tree, and heap sorting. Give you the ability of handwritten red-black trees.
3. Graph structure, including the adjacency list storage representation of the graph structure, depth-first search and breadth-first search, finding the Euler path in the graph, topological sorting, maximum connected components, minimum spanning tree problem, and shortest single source Path problem. It also provides dynamic debugging of these classic graph algorithms.
4. The data structure introductory class will talk about the problem of the Tower of Hanoi. The algorithm that solves this problem is often recursive. This app provides dynamic debugging of the Tower of Hanoi problem, so you can no longer be confused about the recursive calls of the Tower of Hanoi.
- Apple App Store
- Free
- Education
Store Rank
- -
CLRS.Helper[Lite] VS. 
Data Structure DisplayMarch 15, 2025