Computational Complexity vs DSA Master

This app demonstrates the basic principles of computational complexity. The growth of a few typical Big-O functions are illustrated with an interactive graph, and live demonstrations of sorting algorithms can be run using randomly generated data. This app was developed at SUNY Binghamton, by Prof. Patrick H. Madden. Version 1.1 is an expansion on this, with the assistance a few students (primarily Keith Gardner, and undergrad, and Anthony Canino, an MS grad). We're working on the app as a fun project, and as a way to introduce ACM student group members to iOS programming. The source for the app is available on Github; we'll be adding more algorithms and things, and if you're interested in helping out with the development, let us know! https://github.com/keithgardner2/complexity Yay computational complexity! Yay Hartmanis and Stearns!

Master algorithms and data structures with a comprehensive learning platform for computer science students, software engineers, and technical interview preparation. COMPREHENSIVE LEARNING PLATFORM Explore 50+ data structures and algorithms with interactive visualizations, executable code examples, and hands-on practice challenges. From fundamental arrays and linked lists to advanced graph algorithms. INTERACTIVE CODE EXECUTION • Live Code Playground - Write, edit, and execute code in the app • Multi-Language Support - Run code in Python, JavaScript, Java, C++, Kotlin, Dart, and Go • Real-Time Execution Results - See output, errors, and execution time • Syntax Highlighting - Professional code editor with language-specific highlighting • Code Copy & Share - Easily copy code examples or share ANIMATED ALGORITHM VISUALIZATIONS • Step-by-Step Animations - Watch algorithms execute with detailed animated visualizations • Interactive Controls - Play, pause, replay, and control animation speed • Full-Screen Mode - Immersive visualization experience • Visual Data Flow - See how data structures transform during algorithm execution • Multiple Visualization Types - Sorting, searching, tree traversal, graph algorithms COMPREHENSIVE CODE EXAMPLES • 8 Programming Languages - Learn from implementations in Python, JavaScript, Java, C++, Kotlin, Dart, Go, and more • Production-Ready Code - Well-structured, commented code examples • Language Comparison - Compare implementations across different languages • Copy to Playground - Instantly load examples into the code playground • Complexity Analysis - Detailed time and space complexity analysis MODERN INTERFACE & NAVIGATION • Topic Detail Pages - Comprehensive views with Overview, Code, and Visualize sections • Advanced Search & Filtering - Find topics by category, difficulty, or learning path • Smart Recommendations - Personalized topic suggestions • Bookmarks & Notes - Save favorite topics and add personal notes PROGRESS TRACKING & ANALYTICS • Learning Analytics - Track topics completed, challenges solved, and study time • Achievement System - Unlock achievements as you progress • Study Streaks - Build consistent learning habits with daily streak tracking • Study Goals - Set and monitor daily and weekly learning objectives • Performance Insights - Detailed analytics on learning patterns PRACTICE & CHALLENGES • Daily Challenges - New coding challenges every day with varying difficulty levels • Practice Problems - Extensive collection of problems to test understanding • Difficulty Levels - Problems categorized as Easy, Medium, and Hard • Challenge Tracking - Monitor completion rate and improvement COMPREHENSIVE CONTENT LIBRARY Data Structures: Arrays, Dynamic Arrays, Linked Lists, Stacks, Queues, Deques, Hash Tables, Trees (Binary, BST, AVL, Red-Black, Segment, Fenwick), Heaps, Tries, Suffix Trees, Graphs Algorithms: Sorting (Bubble, Selection, Insertion, Merge, Quick, Heap, Topological), Searching (Linear, Binary), Graph Algorithms (DFS, BFS, Dijkstra's, Bellman-Ford, Floyd-Warshall, Kruskal's, Prim's), String Matching (KMP, Rabin-Karp), Tree Traversal ADDITIONAL FEATURES • Offline Access - All content available offline for learning anywhere • Dark Mode Support - Comfortable studying experience in any lighting • Time Complexity Charts - Visual comparisons of algorithm performance • Related Topics - Discover connected concepts and build understanding • Accessibility - Full VoiceOver support and accessibility features • Computer Science Students - Master fundamentals and advanced topics • Software Engineers - Strengthen algorithmic thinking and problem-solving • Technical Interview Preparation - Comprehensive coverage of interview questions • Self-Learners - Structured learning path from beginner to expert • Competitive Programmers - Advanced algorithms and optimization techniques