• Performance: optimized encode/decode for order-1, order-2 (and order-3) context models.
  • ContextModel and ContextState:
    • Added _LazyContextModel base class that allocates one Fenwick tree per
      context lazily, on first use, instead of eagerly creating a tree for
      every possible context.
    • init/reset now cost is proportional to the contexts actually used
      rather than to the full context space (size² for order-2, more for
      order-3), eliminating millions of wasted operations per call.
    • Recycled trees are reused via an internal pool to avoid re-allocation
      across encode/decode runs.
    • ContextModelOrder1/Order2/Order3 now extend _LazyContextModel and
      flatten their context space into a single slot table; output is
      byte-identical to the previous implementation.
  • Fenwick:
    • Maintains a parallel direct-frequency array, so single-symbol frequency
      lookups (freqOf) are O(1). This removes one of the two cumulative tree
      walks per symbol in encode.
    • Added findWithLow, which decodes a symbol and returns its lower
      cumulative bound (sum(symbol - 1)) in a single descent, removing two
      tree walks per symbol in decode.
    • init now builds the all-ones tree directly in O(n) (each node i holds
      i & -i) instead of O(n log n), the dominant cost when many contexts are
      visited (e.g. high-order models on high-entropy data: ~4–5x faster).
    • rescale and toFrequencyList now use the direct-frequency array
      (O(n) instead of O(n log n)).
• Added benchmark/arithmetic_coder_benchmark.dart to track compression ratio
  and encode/decode throughput across orders and datasets for future metrics.
• Tests:
  • Added test/fenwick_test.dart covering the direct-frequency array,
    freqOf, findWithLow, the O(n) init, rescale/rebuild/reset sync,
    and the sum/cumulative invariants (including through many rescales).
  • Added test/context_model_test.dart covering the factory, totalSize,
    contextIndex mapping, lazy allocation, order-3 bucketing, and pool reuse
    across reset/init.
  • Extended test/arithmetic_coder_test.dart with cached-model reuse across
    sequential calls, deterministic re-encoding, and rescale-triggering inputs.

• Performance: optimized encode/decode for order-1, order-2 (and order-3) context models.
  • ContextModel and ContextState:
    • Added _LazyContextModel base class that allocates one Fenwick tree per context lazily, on first use, instead of eagerly creating a tree for every possible context.
    • init/reset now cost is proportional to the contexts actually used rather than to the full context space (size² for order-2, more for order-3), eliminating millions of wasted operations per call.
    • Recycled trees are reused via an internal pool to avoid re-allocation across encode/decode runs.
    • ContextModelOrder1/Order2/Order3 now extend _LazyContextModel and flatten their context space into a single slot table; output is byte-identical to the previous implementation.
  • Fenwick:
    • Maintains a parallel direct-frequency array, so single-symbol frequency lookups (freqOf) are O(1). This removes one of the two cumulative tree walks per symbol in encode.
    • Added findWithLow, which decodes a symbol and returns its lower cumulative bound (sum(symbol - 1)) in a single descent, removing two tree walks per symbol in decode.
    • init now builds the all-ones tree directly in O(n) (each node i holds i & -i) instead of O(n log n), the dominant cost when many contexts are visited (e.g. high-order models on high-entropy data: ~4–5x faster).
    • rescale and toFrequencyList now use the direct-frequency array (O(n) instead of O(n log n)).
• Added benchmark/arithmetic_coder_benchmark.dart to track compression ratio and encode/decode throughput across orders and datasets for future metrics.
• Tests:
  • Added test/fenwick_test.dart covering the direct-frequency array, freqOf, findWithLow, the O(n) init, rescale/rebuild/reset sync, and the sum/cumulative invariants (including through many rescales).
  • Added test/context_model_test.dart covering the factory, totalSize, contextIndex mapping, lazy allocation, order-3 bucketing, and pool reuse across reset/init.
  • Extended test/arithmetic_coder_test.dart with cached-model reuse across sequential calls, deterministic re-encoding, and rescale-triggering inputs.

v1.0.5 Latest

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• ArithmeticCoder:

  • Exposed buildContextModel method to allow customization of the context model creation.
  • Renamed _buildModels to _buildContextModelCached and updated to use buildContextModel.
  • Updated decode method to use models.eof symbol dynamically instead of hardcoded 256.

• ContextModel and ContextState:

  • Added support for order-3 context model:
    • Added ContextStateOrder3 with three previous symbols.
    • Added ContextModelOrder3 with a 3D Fenwick tree structure and a shrink factor to reduce memory usage.
  • Added order getter to ContextState and ContextModel to indicate the model order.
  • Added static maxContextOrder constant (value 3) to ContextModel.
  • Updated factory constructor in ContextModel to support order 3.
  • Updated all context state classes to implement order getter.
  • Updated all context model classes to implement order getter.
  • ContextModelOrder3:
    • Uses a 3D list of Fenwicks with size reduction on the 3rd dimension.

• ArithmeticCoder:

  • Exposed buildContextModel method to allow customization of the context model creation.
  • Renamed _buildModels to _buildContextModelCached and updated to use buildContextModel.
  • Updated decode method to use models.eof symbol dynamically instead of hardcoded 256.

• ContextModel and ContextState:

  • Added support for order-3 context model:
    • Added ContextStateOrder3 with three previous symbols.
    • Added ContextModelOrder3 with a 3D Fenwick tree structure and a shrink factor to reduce memory usage.
  • Added order getter to ContextState and ContextModel to indicate the model order.
  • Added static maxContextOrder constant (value 3) to ContextModel.
  • Updated factory constructor in ContextModel to support order 3.
  • Updated all context state classes to implement order getter.
  • Updated all context model classes to implement order getter.
  • ContextModelOrder3:
    • Uses a 3D list of Fenwicks with size reduction on the 3rd dimension.

v1.0.4

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• Fenwick - reduce memory usage:
  • Updated _tree field initialization to use typed lists (Uint8List, Uint16List, Uint32List, Uint64List) based on the bit length of maxTotal for memory efficiency.
  • Added private static method _buildIntList to create appropriate typed list for frequency storage.
  • Adjusted computeMaxTotal to return (1 << (precision ~/ 2)) - 1 instead of 1 << (precision ~/ 2) to correctly compute maximum total frequency.
  • Changed _tree initialization from List.filled to use _buildIntList in constructor.

• Fenwick - reduce memory usage:
  • Updated _tree field initialization to use typed lists (Uint8List, Uint16List, Uint32List, Uint64List) based on the bit length of maxTotal for memory efficiency.
  • Added private static method _buildIntList to create appropriate typed list for frequency storage.
  • Adjusted computeMaxTotal to return (1 << (precision ~/ 2)) - 1 instead of 1 << (precision ~/ 2) to correctly compute maximum total frequency.
  • Changed _tree initialization from List.filled to use _buildIntList in constructor.

v1.0.3

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• Added context modeling support to ArithmeticCoder:

  • Added order parameter to specify finite-order Markov models (0, 1, or 2).
  • Integrated ContextModel abstraction with adaptive Fenwick trees per context.
  • Updated encoding and decoding to use context-dependent frequency models.
  • Added toString override to ArithmeticCoder showing order and model size.

• ContextModel:

  • Introduced abstract ContextModel with factory constructor for orders 0, 1, and 2.
  • Implemented ContextModelOrder0, ContextModelOrder1, and ContextModelOrder2 with corresponding ContextState classes.
  • Each model maintains Fenwick trees for symbol frequencies per context.
  • Adaptive frequency updates and context state transitions implemented.

• arithmetic_coder.dart:

  • Refactored to use ContextModel for symbol frequency management.
  • Encoding and decoding now maintain and update context states.
  • Added detailed comments on algorithm and context modeling.

• example/arithmetic_coder_example.dart:

  • Updated example to use ArithmeticCoder(order: 2).
  • Increased input repetition count for better compression demonstration.
  • Added output of compression ratio and integrity check.
  • Added helper _listEquals for byte list comparison.

• test/arithmetic_coder_test.dart:

  • Parameterized tests to run for orders 0, 1, and 2.
  • Removed redundant ArithmeticCoder instantiations inside tests.
  • Verified encode-decode correctness and compression ratio for all orders.

• pubspec.yaml:

  • Bumped version to 1.0.1.

• Added context modeling support to ArithmeticCoder:

  • Added order parameter to specify finite-order Markov models (0, 1, or 2).
  • Integrated ContextModel abstraction with adaptive Fenwick trees per context.
  • Updated encoding and decoding to use context-dependent frequency models.
  • Added toString override to ArithmeticCoder showing order and model size.

• ContextModel:

  • Introduced abstract ContextModel with factory constructor for orders 0, 1, and 2.
  • Implemented ContextModelOrder0, ContextModelOrder1, and ContextModelOrder2 with corresponding ContextState classes.
  • Each model maintains Fenwick trees for symbol frequencies per context.
  • Adaptive frequency updates and context state transitions implemented.

• arithmetic_coder.dart:

  • Refactored to use ContextModel for symbol frequency management.
  • Encoding and decoding now maintain and update context states.
  • Added detailed comments on algorithm and context modeling.

• example/arithmetic_coder_example.dart:

  • Updated example to use ArithmeticCoder(order: 2).
  • Increased input repetition count for better compression demonstration.
  • Added output of compression ratio and integrity check.
  • Added helper _listEquals for byte list comparison.

• test/arithmetic_coder_test.dart:

  • Parameterized tests to run for orders 0, 1, and 2.
  • Removed redundant ArithmeticCoder instantiations inside tests.
  • Verified encode-decode correctness and compression ratio for all orders.

• pubspec.yaml:

  • Bumped version to 1.0.1.

v1.0.2

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1.0.0

• Initial version.

• Initial version.

v1.0.0

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