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Published 32 days ago β€’ verified publisherkidpech.appβ€’ Latest: 0.2.5
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Metadata

Professional algorithm selection companion with intelligent strategy selection, built-in benchmarking, and performance optimization. Features Clean Architecture, comprehensive error handling, and prod [...]

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Changelog #

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased] #

Added #

  • QuickSort algorithm implementation
  • HeapSort algorithm implementation
  • Enhanced error handling with sealed classes
  • Performance regression testing
  • Contract testing for mocks
  • Memory usage tracking and limits
  • Fallback mechanisms for strategy failures

Changed #

  • Improved async support integration
  • Enhanced documentation coverage

0.1.0 - 2025-09-01 #

Added #

  • 🎯 Intelligent Algorithm Selection: Context-aware strategy selection based on data characteristics
  • ⚑ Performance-Focused Architecture: Zero-allocation hot paths with traditional loops
  • πŸ—οΈ Clean Architecture Implementation: Complete DDD + Clean Architecture with 4 distinct layers
  • πŸ“Š Built-in Algorithm Library:
    • 6 sorting strategies (InsertionSort, InPlaceInsertionSort, BinaryInsertionSort, MergeSort, IterativeMergeSort, HybridMergeSort)
    • 2 search strategies (LinearSearch, BinarySearch)
  • πŸ”§ Comprehensive Infrastructure:
    • Statistical benchmarking with HarnessBenchmarkRunner, SimpleBenchmarkRunner, MockBenchmarkRunner
    • Isolate execution with DartIsolateExecutor, StubIsolateExecutor, MockIsolateExecutor
    • Flexible logging with ConsoleLogger, SilentLogger, BufferedLogger
  • πŸ§ͺ Production-Ready Features:
    • Functional error handling with Result<T, Failure> pattern
    • Resource management for isolate execution
    • Configurable logging levels and statistics
  • πŸ”„ Advanced Capabilities:
    • CPU-intensive operations in isolates with timeout support
    • Performance measurement and comparison tools
    • Custom strategy registration system
  • πŸ“ Developer Experience:
    • Simple facade API (AlgoSelectorFacade.development())
    • Builder pattern configuration (AlgoMate.createSelector())
    • Comprehensive documentation and examples
    • Type-safe strategy storage and execution

Technical Details #

  • Architecture: Domain-Driven Design with Clean Architecture principles
  • Layers: Domain (6 files), Application (4 files), Infrastructure (10 files), Interface (2 files)
  • Dependencies: Flutter, Meta for annotations
  • Development Dependencies: Flutter Test, Benchmark Harness, Flutter Lints
  • Total Files: 25 implementation files
  • Test Coverage: Basic unit tests with integration scenarios
  • Performance: Optimized for speed with zero-allocation hot paths

Breaking Changes #

  • N/A (Initial release)

Deprecated #

  • N/A (Initial release)

Removed #

  • N/A (Initial release)

Fixed #

  • N/A (Initial release)

Security #

  • N/A (Initial release)

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Publisher

verified publisherkidpech.app

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Metadata

Professional algorithm selection companion with intelligent strategy selection, built-in benchmarking, and performance optimization. Features Clean Architecture, comprehensive error handling, and production-ready algorithms for sorting and searching operations.

Repository (GitHub)
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Topics

#algorithms #sorting #searching #performance #optimization

Documentation

Documentation

Funding

Consider supporting this project:

github.com

License

unknown (license)

Dependencies

meta

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