{"id":23589241,"url":"https://github.com/ewdlop/datastructure-algorithm-note","last_synced_at":"2025-06-19T15:37:59.128Z","repository":{"id":269677010,"uuid":"900552269","full_name":"ewdlop/DataStructure-Algorithm-Note","owner":"ewdlop","description":"Software -\u003e Hardware for performance; Hardware -\u003e Software for robustness; ","archived":false,"fork":false,"pushed_at":"2025-02-16T12:29:19.000Z","size":267,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-16T13:37:57.058Z","etag":null,"topics":["contextualized-representation","desing-pattern","desing-principles-and-methods","good-practices","save-lives"],"latest_commit_sha":null,"homepage":"","language":"C#","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ewdlop.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-12-09T02:56:17.000Z","updated_at":"2025-02-16T12:29:22.000Z","dependencies_parsed_at":"2025-02-04T07:23:26.814Z","dependency_job_id":"b5da7d97-45cc-4e94-9709-dce90bd2c6a5","html_url":"https://github.com/ewdlop/DataStructure-Algorithm-Note","commit_stats":null,"previous_names":["ewdlop/datastructure-algorithm-note"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ewdlop%2FDataStructure-Algorithm-Note","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ewdlop%2FDataStructure-Algorithm-Note/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ewdlop%2FDataStructure-Algorithm-Note/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ewdlop%2FDataStructure-Algorithm-Note/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ewdlop","download_url":"https://codeload.github.com/ewdlop/DataStructure-Algorithm-Note/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239419762,"owners_count":19635447,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["contextualized-representation","desing-pattern","desing-principles-and-methods","good-practices","save-lives"],"created_at":"2024-12-27T06:13:32.981Z","updated_at":"2025-02-18T06:24:24.440Z","avatar_url":"https://github.com/ewdlop.png","language":"C#","funding_links":[],"categories":[],"sub_categories":[],"readme":"# DataStructureNote\n\n## Overview\nThis project is a collection of data structures and algorithms implemented in C#. It includes various data structures such as graphs, inverted indexes, ropes, and more. The project also provides implementations of common algorithms like bubble sort.\n\n## Data Structures and Algorithms\n### Data Structures\n- **Graph**: A class representing a graph data structure with methods to add vertices, add edges, display the graph, and invert the graph.\n- **Inverted Index**: A class representing an inverted index, which is used to map terms to the documents that contain them.\n- **Rope**: A class representing a rope data structure, which is a binary tree used to store and manipulate strings efficiently.\n\n### Algorithms\n- **Bubble Sort**: An implementation of the bubble sort algorithm with various extension methods for sorting collections.\n\n## Building and Running the Project\nTo build and run the project, follow these steps:\n1. Ensure you have .NET 9.0 SDK installed on your machine.\n2. Clone the repository: `git clone https://github.com/ewdlop/DataStructure-Algorithm-Note.git`\n3. Navigate to the project directory: `cd DataStructure-Algorithm-Note/CSharpDataStructureAndAlogrithm`\n4. Build the project: `dotnet build`\n5. Run the project: `dotnet run --project ConsoleApp1`\n\n## Examples\n### Bubble Sort\nThe following example demonstrates how to use the bubble sort implementation provided in the project:\n```csharp\nusing Algorithm;\n\nList\u003cint\u003e numbers = new List\u003cint\u003e { 5, 3, 8, 4, 2 };\nIEnumerable\u003cint\u003e sortedNumbers = numbers.AsBubbleSortEnumerable();\nforeach (int number in sortedNumbers)\n{\n    Console.WriteLine(number);\n}\n```\n\n## Dependencies\nThis project requires the following tools and libraries:\n- .NET 9.0 SDK\n\n## Contributing\nContributions are welcome! If you would like to contribute to the project, please follow these guidelines:\n1. Fork the repository.\n2. Create a new branch for your feature or bugfix.\n3. Make your changes and commit them with descriptive commit messages.\n4. Push your changes to your forked repository.\n5. Create a pull request to the main repository.\n\nIf you encounter any issues or have any questions, please open an issue on the GitHub repository.\n\n# Here are some ideas for optimizing disk-based data structures:\n\n- Use LSM trees for write-optimized storage\n- Implement circular buffers for streaming data\n- Design cache-aware algorithms for better I/O patterns\n\n- ImplemeImplement log-structured merge trees for efficient writes\n- Use B+ trees for optimized range queries and disk access\n- Design append-only data structures for sequential writes\n- Implement copy-on-write B-trees for concurrent access\n- Create disk-based skip lists for efficient searching\n- Use fractal trees to reduce write amplification\n- Design external memory priority queues\n- Implement disk-based hash tables with overflow chains\n- Create memory-mapped vector structures\n- Use R-trees for spatial data on disk\n\nAdvanced optimizations:\n\n- Implement buffer pools for frequently accessed data\n- Design page-aligned data structures\n- Create compression-friendly storage formats\n- Use write-ahead logging for crash recovery\n- Implement disk-based bloom filters\n\nPerformance considerations:\n\n- Optimize for sequential access patterns\n- Minimize random I/O operations\n- Use batching to improve throughput\n- Implement efficient garbage collection\n- Design for cache locality\n\nAdditional data structure optimizations:\n\n- Implement disk-based sorted arrays\n- Design hybrid memory-disk hash tables\n- Create versioned B-trees for temporal data\n- Use extendible hashing for dynamic growth\n- Implement disk-based tries for string data\n- Design chunked storage for large objects\n- Create disk-based queues with circular buffers\n- Use bitmap indexes for column-oriented data\n- Implement partitioned hash tables\n- Design log-structured hash tables\n\nSpecialized structures:\n\n- Create disk-based suffix arrays\n- Implement external memory quadtrees\n- Design persistent red-black trees\n- Use disk-based cuckoo hash tables\n- Implement external memory KD-trees\n\nConcurrency optimizations:\n\n- Design lock-free disk structures\n- Implement MVCC for concurrent access\n- Create thread-safe buffer managers\n- Use optimistic concurrency control\n- Design concurrent B-link trees\n\nI/O optimizations:\n\n- Implement asynchronous I/O patterns\n- Design prefetching strategies\n- Create intelligent page replacement\n- Use direct I/O for better control\n- Implement vectored I/O operations\n\nMemory management:\n\n- Design slab allocators for disk blocks\n- Implement buddy system allocation\n- Create segregated free lists\n- Use reference counting for cleanup\n- Design compacting storage strategies\n\nCompression techniques:\n\n- Implement dictionary compression\n- Use delta encoding for similar records\n- Design run-length encoding schemes\n- Create prefix compression methods\n- Implement block-level compression\n\nCaching strategies:\n\n- Design multi-level cache hierarchies\n- Implement adaptive cache policies\n- Create cache-oblivious algorithms\n- Use predictive cache warming\n- Design cache-conscious indexing\n\nRecovery mechanisms:\n\n- Implement checkpoint-recovery systems\n- Design redo logging strategies\n- Create shadow paging schemes\n- Use journaling for consistency\n- Implement ARIES-style recovery\n\nPartitioning strategies:\n\n- Design range partitioning schemes\n- Implement hash partitioning\n- Create composite partitioning\n- Use list partitioning methods\n- Design round-robin partitioning\n\nMonitoring and metrics:\n\n- Implement I/O statistics tracking\n- Design performance counters\n- Create bottleneck detection\n- Use adaptive optimization\n- Implement resource utilization monitoring\n\nAdvanced features:\n\n- Design time-travel queries\n- Implement incremental maintenance\n- Create self-tuning structures\n- Use hybrid memory-disk algorithms\n- Design zero-copy data paths\n\nSpecialized indexes:\n\n- Implement inverted indexes\n- Design spatial indexes\n- Create temporal indexes\n- Use multi-dimensional indexes\n- Implement partial indexes\n\nQuery optimization:\n\n- Design cost-based optimizers\n- Implement index selection\n- Create join optimization\n- Use materialized views\n- Design query rewriting rules\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fewdlop%2Fdatastructure-algorithm-note","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fewdlop%2Fdatastructure-algorithm-note","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fewdlop%2Fdatastructure-algorithm-note/lists"}