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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

  • Modular, streaming language-binding boundary. Added the versioned vinary-tree-interop retained-resource ABI and changed liblevenshtein's bindings to consume vt.dictionary.v1 resources instead of owning libdictenstein dictionary constructors or CRUD. Query cursors return leased, contiguous batches (or a zero-copy reducer callback), retain an O(1) query-start snapshot, and may outlive both the transducer and source handle. C/C++, Python custom providers, Java 22 FFM, Clojure, TypeScript, and ClojureScript facades form the first migration wave. Example and property tests keep one partially consumed cursor alive across insert, remove, update, clear, compact, and checkpoint mutations; C ABI tests additionally enforce lease lifetime and one callback per batch. Native CI covers Linux x86_64 and aarch64, macOS aarch64, Windows x86_64, BSD targets, and experimental armv7.

Changed

  • Moved the binding architecture to per-project packages with one shared ABI. Native packages remain modular; the JavaScript/WASM/WASI surface uses the deliberate @vinary-tree/vinary-tree umbrella runtime so related projects share one resource table. Tier 2 and Tier 3 bindings, including OCaml and Fortran, are withheld from publication until their older dictionary-owning facades complete the same migration.

[0.10.0] - 2026-08-03

Changed

  • Split the liblevenshtein executable, REPL, filesystem grep pipeline, and archive/document extractors into the new liblevenshtein-cli crate.
  • Removed the cli, grep-compression, grep-archives, and grep-documents feature families and their application-only dependencies.
  • Kept the reusable in-memory phonetic grep engines and parallel-grep in the library.

Removed

  • Removed MittonCorpus::load_birkbeck_zip; archive-backed corpus fixture loading is no longer part of the library API.

Added

  • Alignment-expressible Class-A presets and references. OperationSet::{hamming,indel,bounded_skip}, Unicode-scalar Hamming, and full/banded insertion-deletion distances expose exact reference semantics. OperationSet::validate enforces progress, finite non-negative weights, zero-cost length preservation, checked aggregation, and a 4,096-unit resource ceiling before generalized traversal. Twenty-thousand generated cases, an exhaustive 42,395-pair Birkbeck gate, runnable examples, and Rocq/Dafny/Verus/Z3/cvc5/TLA+ models cross-check the invariants. Dedicated dictionary walkers remain unshipped because the preregistered structural reduction threshold was not met.

  • Exact affine-gap dictionary search. AffineGapParams, Transducer::query_affine, scaled string/token entry points, and QueryBuilder::affine_gap expose Gotoh's three-layer recurrence with exact decimal scaling. The lazy kernel implements layer-aware completion, operation-derived windows, and formally verified same-index B-4 subsumption; an independent quadratic oracle and 2,000-case differential, invariant, backend, and policy properties enforce complete result-map and cost equality. Rocq, Dafny, Verus, Z3/cvc5, and TLA+ cross-check the core invariants. Cross-index B-5 pruning remains deliberately disabled, with its minimized unfused-transition counterexample retained as a regression seed.

  • Budget-bounded unrestricted Damerau–Levenshtein search. Algorithm::DamerauLevenshtein, Transducer::with_damerau_levenshtein, and the full Lowrance–Wagner reference DP add true history-composing transpositions without changing OSA. A DamerauPending macro chain preserves all Standard paths and refines entry/extension/resolution exactly. Serde, FromStr, FFI, WASM, REPL, examples, Criterion, 2,000-case differential and metric properties, a 42,395-pair Birkbeck gate, and Rocq/Verus/SMT/TLA+ evidence ship together. The compact delta ceiling is explicit at 255 and unsupported weighted/product engines fail rather than silently projecting to another distance.

  • Zero-width PositionKind/AutomatonVariant seam. Position remains 24 bytes on 64-bit targets while typed continuation kind and payload now participate in its total order. Legacy transition and subsumption policy is selected once per repeated dictionary-edge loop and statically specialized inside the position loop; the one-position API uses one direct match and an owned return. Algorithm is now #[non_exhaustive]; downstream exhaustive matches require a wildcard arm. Property, Rocq, Verus, Z3/cvc5, and TLA+ gates pass. All six pre-registered Criterion suites pass across 423 cases; the stricter byte-identical-disassembly hypothesis is retained as a documented negative result because its probe also measured intentional payload and ownership changes. A separate optimized-LLVM-IR audit passes by showing that the constant-Standard probe retains no runtime selector, non-Standard leaf, or selector switch.

  • Observable elastic-search pruning and a shared UCR harness. ElasticSearchStats and search_knn_with_stats report prefix, column, candidate, exact-evaluation, cutoff, node, and edge counts without changing ordered results. The generalized elastic-ucr --measure experiment runs MSM, ERP, TWED, discrete Fréchet, or banded DTW under one preregistered 51-dataset protocol, with flat/trie distance agreement, process peak memory, checksums, paired case outcomes, and deterministic summaries. Rocq, Verus, Z3/cvc5, example, integration, and 2,000-case property tests enforce result transparency and counter partitions.

  • Exact TWED kernel and trie search. TwedConfig implements unit-spaced Time Warp Edit Distance with a two-row cutoff DP, carry-aware interval columns, and the $|m-n|*lambda$ candidate bound. MetricTwedConfig validates finite nu > 0 and lambda >= 0 and alone supplies the static metric witness; the unrestricted zero-stiffness family remains available without an unsound marker. Differential, example, property, integration, Rocq, Verus, Z3/cvc5, documentation, and registered benchmark coverage ship with the kernel.

  • Ordered cost-monoid seam. CostMonoid provides a fixed minimum choice, total ordering, inclusive budget predicate, and lawful accumulation for UnitCost, additive WeightedCost, and minimax BottleneckCost. CostScale converts decimal operation weights into checked exact integer costs without silent rounding or overflow. Rocq, Verus, Z3/cvc5, and property tests cover the algebra and explicitly delimit IEEE-754 rounding.

  • Repaired GeneralizedAutomaton acceptance. Runtime operations now drive the complete alignment, including empty-side behavior, multi-scalar restrictions, and adjacent transposition. Fractional weights accumulate in an exact scaled-integer domain instead of truncating to zero. Fallible APIs report invalid weights, overflow, and the one-million-cell resource guard; Hamming, indel, bounded-skip, Unicode, and standard semantics are checked against independent references and formal models.

  • VersionedQueryCache (liblevenshtein::transducer::VersionedQueryCache) — an opt-in, dictionary-version-tied cross-query result cache that memoizes (query, max_distance) → results and self-invalidates on a dictionary version bump (correct for dynamic dictionaries). On repeated-query workloads a cache hit skips the automaton state-transition inner loop (≈80% of query CPU per AMD uProf profiling); measured ≈11,500× faster on a pre-registered repeated-query benchmark (Welch t p≈3×10⁻¹⁷⁰, Cohen's d≈−81), with cached results proven identical to uncached. It does not touch the hot path, so unique-query workloads are unaffected. See docs/scientific-ledger/version-tied-cross-query-result-cache-*.md.

Fixed

  • Zipper whole-term distance inference now uses query length. AutomatonZipper::infer_distance previously passed dictionary depth to a state method whose argument is query length, undercharging shorter terms and overcharging longer ones. Node, intersection, and zipper traversal now agree; the true-Damerau separator CAABC is retained at distance 2.
  • Weighted edit distance now honours non-unit insertion/deletion costs. The float-weighted transducer (CandidateIteratorF64 / OperationCostsF64) previously returned wrong distances whenever insertion or deletion differed from 1.0: trailing deletions needed to reach acceptance were charged at unit cost, and a padded look-ahead window could emit a spurious past-query-end position whose cheaper substitution cost was reported instead of the true edit distance. StateF64::infer_distance now charges trailing deletions at deletion cost and rejects positions with term_index > query_length. Unit-cost results are unchanged.
  • Weighted subsumption no longer over-prunes for non-unit costs. PositionF64::subsumes scales the index-realignment bound by max(insertion, deletion), so a position leading to the only in-budget match is no longer discarded when insertion/deletion > 1.
  • GeneralizedPosition ordering is now consistent with its derived Eq/Hash (tiebreaks on entry_char), restoring the Ord/Eq contract binary_search relies on.
  • Deterministic tie ordering for MSM empty-/non-finite-query and hybrid brute-force searches (equal-distance results no longer depend on HashMap iteration order).

Changed

  • Crate-wide numeric hardening: implicit wraparound, lossy float→int casts, overloaded sentinels, and unchecked capacity arithmetic replaced with checked/saturating/provably-bounded conversions (the sole intentional wrapping_add — Myers' bit-parallel recurrence — is documented).
  • Quantization (time_series::encoding) explicitly clamps NaN/±∞/out-of-range inputs; OperationCostsF64::is_valid also rejects non-finite costs.
  • Hardened UTF-8 span handling in CLI/grep and checked length/capacity conversions in the LLRE/LLEV/compression decoders; added non-ASCII regression coverage.
  • Documented Algorithm::MergeAndSplit as an intentional wildcard over-approximation, and phonetic_weight / NFA Transition.weight as reserved (not applied to matching cost).

See docs/design/numeric-and-weighted-cost-hardening.md for the full invariant catalogue and verification methodology.

[0.9.1] - 2026-06-15

Added

  • UTF-8 dictionary types now re-exported from the prelude. DoubleArrayTrieChar, DynamicDawgChar, and SuffixAutomatonChar are now reachable via liblevenshtein::prelude (previously only their ASCII counterparts and ScdawgChar were), closing a gap where the UTF-8 dictionaries were unreachable through liblevenshtein's public surface.
  • MORK-style zero-plumbing fuzzy queries over a bare PathMap. examples/mork_fuzzy_query.rs runs a Transducer over libdictenstein's new PathMapSnapshot / PathMapRef (borrowed, zero-copy) and a subtrie-scoped from_trie_ref — no trie copy, no lock. tests/pathmap_snapshot_tests.rs proves the borrowed dictionary drives the full query stack with no hidden 'static bound, plus transducer-level snapshot isolation and Unicode.
  • benches/pathmap_node_ops_benchmark.rs — node-op micro-benchmarks (transition by depth, edges by fanout, root-snapshot cost, mixed-width char edges) plus comb/deep-node variants (transition_at_depth_branching, edges_at_depth_branching, char_edges_at_depth) that defeat pathmap's path compression to measure the 𝒪(depth)→𝒪(1) node behaviour directly against the frozen pre-rework tree.

Changed

  • PathMap-backed dictionaries are now lock-free over an 𝒪(1) copy-on-write snapshot (libdictenstein's TrieRef rework): queries no longer re-walk the path from the root under a per-operation lock. Existing PathMapDictionary{,Char} usage is behaviorally identical; in-flight queries gain snapshot isolation.
  • libdictenstein reorganized its dictionary families into directory submodules; the deprecated liblevenshtein::dictionary::* re-exports were repointed to the new submodule paths (their names are unchanged).
  • Deprecated liblevenshtein's libdictenstein re-exports in the prelude (the dictionary types, the Dictionary traits, and the factory/substring re-exports). Import these from libdictenstein directly; the convenience re-exports remain available but will be removed in a future release.
  • CI/release dependency resolution split by workflow. Development/CI builds clone the in-development sibling crates (llattice, libdictenstein) so the path dependencies resolve against dev versions; release builds, packaging, and the crates.io publish resolve them from their published versions. The crates.io publish step is now idempotent on re-release.

Dependencies

  • libdictenstein requirement bumped 0.10.2 — its dictionary-family submodule reorg is a breaking module-path change, published as libdictenstein 0.2.0.
  • pathmap requirement widened to >=0.2.2, <0.4 (resolves to 0.2.2 on crates.io; compiles against a local PathMap 0.3.0).

[0.9.0] - 2026-06-10

Removed

  • BREAKING: WFST adapters moved to the new duallity crate. The wfst feature and the liblevenshtein::wfst::* module — LevenshteinWfst, DictionaryBackend, and the universal / WallBreaker / generalized / phonetic WFST variants — were extracted into duallity (which depends on both liblevenshtein and lling-llang), breaking the liblevenshtein ⇄ lling-llang dependency cycle. Migrate use liblevenshtein::wfst::Xuse duallity::X, and depend on duallity instead of enabling the wfst feature. (No crates.io consumer is affected: the old wfst feature was unusable from the registry because its lling-llang dependency was a path dependency.)

Added

Exact MSM-bounded retrieval: MsmTransducer (2026-05-28)

  • Added: time_series::MsmTransducer, an exact Move-Split-Merge similarity index over a trie of quantized reference series. search_range(query, tau) returns exactly { id : MSM(query, ref_id) <= tau } (no false negatives, no false positives) and search_knn(query, k, initial_threshold) the exact k nearest by MSM distance. It walks the trie with an interval-relaxed MSM dynamic program (time_series::msm_interval), prunes subtrees by an admissible column lower bound, and re-scores survivors against the stored full-precision originals — closing the completeness gap of HybridSearchIndex::search_exact, whose lossy Levenshtein pre-filter can drop true MSM-near neighbors.
  • Added: QuantizationConfig::bin_bounds(bin) -> (f64, f64), the admissible per-bin value interval [lo, hi] (extreme bins extend to ±∞), consumed by the interval-MSM bounds.
  • Verification: the admissibility, column-admissibility, and pruning-soundness claims are proved axiom-free in Coq/Rocq (docs/verification/msm/theories/Indexing/{IntervalCost,QuantizationBounds,IntervalColumn}.v) and the trie-walk soundness/completeness is model-checked in TLA+ (docs/verification/tla/MsmTrieSearch.tla). See docs/verification/msm/INTERVAL_MSM.md.

Removed

simd, scdawg-bloom, scdawg-simd Cargo Features Removed (2026-05-22)

  • Removed: simd, scdawg-bloom, scdawg-simd Cargo features.
    • SIMD code is now always compiled on x86_64 targets and dispatched at runtime via is_x86_feature_detected!("avx2") / "sse4.1", with same-module scalar fallbacks. The Cargo feature was redundant — it gated whether the always-correct code compiled at all, not whether SIMD ran (which has always been a runtime decision).
    • The scdawg-bloom and scdawg-simd features had no source-level gates in this crate; they were pass-through delegations to libdictenstein, which removed them in 4b17b43. Their continued presence here had already broken --features simd builds.
    • The #[cfg(feature = "simd")] gates throughout the source tree were converted to #[cfg(target_arch = "x86_64")]. The simd modules (src/distance/simd.rs, src/transducer/simd.rs) are now compiled exclusively on x86_64; the dead non-x86_64 scalar fallbacks inside them have been removed (call sites already select the scalar implementation on non-x86_64).
  • Migration: users with features = ["simd"] in their Cargo.toml should drop it. No behavior change on x86_64; non-x86_64 targets continue to use the scalar implementation automatically.

phonetic::language::rules and dispatch are now feature-gated on embedded-rules

  • The per-language rule aggregator submodule (phonetic::language::rules::*) and the dispatch entry points (rules_for_language, default_language, is_supported, supported_languages) require the embedded-rules Cargo feature. They depend on the per-language phonetic rule modules under phonetic::rules::*, which have always been gated on embedded-rules. Builds without this feature previously failed with unresolved-import errors; they now compile cleanly with the language dispatcher simply absent.

DawgDictionary and OptimizedDawg Deprecated and Removed (2025-12-28)

  • DawgDictionary and OptimizedDawg removed in favor of DynamicDawg and DoubleArrayTrie
    • Static DAWG implementations superseded by superior alternatives:
      • DynamicDawg: Supports online insert/delete/compact with better performance
      • DoubleArrayTrie: Faster O(1) transitions for static dictionaries
    • All references updated across codebase (~50 files)
    • Migration: Replace DawgDictionary::from_terms() or OptimizedDawg::from_terms() with:
      • DynamicDawg::from_terms() for mutable scenarios
      • DoubleArrayTrie::from_terms() for static/read-only scenarios
    • Deleted files: src/dictionary/dawg.rs, src/dictionary/dawg_query.rs, src/dictionary/optimized_dawg.rs
    • Deleted examples: dawg_demo.rs, dawg_query_comparison.rs
    • Deleted benchmarks: dawg_benchmarks.rs
    • Current dictionary backends (12 total):
      • DoubleArrayTrie / DoubleArrayTrieChar - O(1) transitions for static dictionaries
      • DynamicDawg / DynamicDawgChar - Mutable DAWG with online minimization
      • SuffixAutomaton / SuffixAutomatonChar - Substring matching
      • SCDAWG / ScdawgChar - Symmetric Compact DAWG for bidirectional traversal
      • PersistentARTrie / PersistentARTrieChar - Disk-based adaptive radix trie
      • PathMap / PathMapChar - Dynamic trie (feature-gated)

0.8.0 - 2025-12-20

Added

PhoneticNormalizedDictionary (2025-12-22)

  • Phonetic-aware fuzzy dictionary implementing Approach 1 from compositional spelling correction

    • Pre-processes both query and dictionary for maximum query speed
    • Normalizes terms phonetically using Zompist rules at build time
    • Maps normalized forms back to original terms at query time
    • PhoneticNormalizedDictionary::from_terms() - create with default rules
    • PhoneticNormalizedDictionary::from_terms_with_rules() - create with custom rules
    • query() - fuzzy search in normalized space with edit distance tolerance
  • Regex Query Support for grep-like pattern matching

    • query_regex() - match regex patterns against normalized forms
    • query_with_product() - use pre-compiled NFA for repeated queries
    • Supports all regex syntax: alternation, quantifiers, character classes
    • Results mapped back to original dictionary terms
  • Phonetic Pattern Expansion for reverse phonetic matching

    • query_phonetic_pattern() - auto-expand query to match phonetic variants
    • expand_phonetic_alternatives_char() - convert normalized string to regex pattern
    • expand_with_costs() - expand with rule weight tracking
    • Example: "fone" → "(ph|f)one" matching both "fone" and "phone"
  • New Types

    • PhoneticNormalizedCandidate - query result with term, distance, normalized form
    • RegexQueryError - error type for regex operations
  • FuzzyMultiMap Enhancements

    • query_with_distance() - returns matched key, distance, and values
    • Enables efficient phonetic → original term mapping

WASM and WASI Support (2025-12-19)

  • WebAssembly compilation targets
    • Full WASM support for browser and Node.js targets
    • WASI support for server-side WebAssembly runtimes
    • wasm feature flag enables wasm-bindgen bindings
    • wasm-phonetic feature combines WASM with phonetic rules
    • ffi feature exposes C-compatible functions for WASI/native FFI
    • Phonetic spellcheck example includes WASM demo application

LLev - Levenshtein Regular Expressions (2025-11-16 to 2025-12-18)

  • Complete LLev Parser and NFA Engine

    • New domain-specific language for phonetic pattern matching
    • LLRE (Levenshtein Regex) format for compact pattern specification
    • Full regex-like syntax: quantifiers (*, +, ?, {n,m}, {,m}), alternation, grouping
    • Built-in named character classes ([:alpha:], [:digit:], [:vowel:], etc.)
    • Escape shortcuts for common character categories
    • Cycle detection and equivalence set recovery for pattern analysis
  • Phonetic Spellcheck Example

    • Complete demo application with dictionary caching
    • Interactive spellcheck with phonetic similarity matching
    • WASM-compatible version for browser deployment

NFA Optimizer Module (2025-12-15)

  • Automatic NFA Optimization - Reduces NFA size and improves matching performance

    • Epsilon elimination: Removes ε-transitions by computing transitive closure
    • Unreachable state removal: Prunes states not reachable from start
    • Dead state removal: Removes states that cannot reach any final state
    • Transition deduplication: Removes duplicate transitions after epsilon elimination
  • New Types

    • OptimizationConfig: Configuration with full(), quick(), none() presets
    • OptimizationStats: Statistics on optimization results (states/transitions removed)
    • NfaOptimizerChar / NfaOptimizer: Optimizer implementations for char/byte NFAs
  • NFAChar/NFA API Additions

    • optimize(): Apply full optimization
    • optimize_with(config): Apply custom optimization, returns statistics
    • count_epsilon_transitions(): Count ε-transitions in NFA
  • Compiler Integration

    • NFACompilerChar::with_optimization(config): Set optimization configuration
    • NFACompilerChar::without_optimization(): Disable automatic optimization
    • Optimization enabled by default in compile() function
    • 11 unit tests covering all optimization passes

Generic Iterator Support (2025-11-28)

  • Universal iterator interface for all dictionary backends
    • Consistent iteration API across PathMap, DAWG, DoubleArrayTrie, and SuffixAutomaton
    • Both byte-level and character-level variants supported
    • Enables generic algorithms over any dictionary type

Formal Verification (2025-11-15 to 2025-12-17)

  • Levenshtein Automaton Proofs in Coq/Rocq

    • Complete axiom-free proofs for Levenshtein distance properties
    • Triangle inequality proof using Wagner-Fischer trace approach
    • Modular decomposition with 0 Admitted lemmas in extraction
    • Position skipping verification: 50/50 proofs complete
    • Comprehensive trace composition cost bounds
  • Phonetic Rewrite Rules Verification

    • All 5 core theorems proven in Coq
    • OCaml extraction infrastructure for verified code
    • Property-based tests mirroring Coq theorems (proptest)

Performance

NFA Optimizations (2025-12-18)

  • H7+H8+H9 Combined Optimizations - 2-7× speedup for NFA operations

    • H7: State representation optimization
    • H8: Transition table compaction
    • H9: Hot path specialization
  • Phonetic Lexer Optimizations

    • H1: Intern phonetic class names for 7-11% speedup
    • H2: Stack-based ASCII lowercase for 3-4% cold start improvement
    • H3 (rejected): FxHashMap caused 10-15% regression
    • H4 (rejected): Alternative approach showed no improvement

Phonetic Matching Optimizations (2025-11-17 to 2025-11-25)

  • Position Skipping Optimization - Up to 26.6× speedup

    • Skip ahead to first potential match position in phonetic patterns
    • Reduces unnecessary state exploration
    • Opt-in via explicit API call (see Deprecated section)
  • Phonetic Rules Allocation Elimination - 27-30% speedup

    • Eliminated string allocations in successor methods
    • H2 conditional optimization with zero overhead

Changed

API Changes

  • apply_rules_seq_opt deprecated - Position skipping is now opt-in
    • Use apply_rules_with_skip() for position skipping behavior
    • Default apply_rules() uses standard sequential matching
    • Migration: Replace apply_rules_seq_opt calls with explicit skip API

Fixed

Bug Fixes

  • M-type merge index overflow - Fixed overflow bug in generalized automaton module
    • Added comprehensive property tests to prevent regression
    • Affects phonetic split operations with accumulated errors

Documentation

Integration Architecture (2025-11-26 to 2025-12-02)

  • MORK and PathMap Integration

    • Comprehensive MeTTa query examples
    • Three-layer integration architecture clarification
    • Extended architecture layers documentation
  • WFST Documentation

    • Weighted finite-state transducer implementation comparison
    • Cross-references to MeTTaIL correction documentation
  • Theoretical Foundations

    • Pedagogical content for compiler implementers
    • Semantic type checking documentation
    • Dialogue, LLM integration, and agent learning patterns

Verification Documentation

  • Comprehensive proof status tracking
    • Admitted lemmas analysis and resolution
    • Phase-by-phase completion status
    • Modular proof index

CI/CD

Build Infrastructure (2025-12-19)

  • OCR Support in CI
    • Tesseract and Leptonica installation for document processing
    • Ubuntu workflow updates for libtesseract-dev

0.7.0 - 2025-11-15

Added

Phase 3b: Phonetic Operations - Partial Implementation (2025-11-14)

  • Phonetic Split Operations ⟨1,2⟩ (92% complete - 22/24 tests passing)

    • Implemented split operations for single-to-multi-character phonetic transformations (k→ch, t→th, s→sh, f→ph)
    • Added entry_char field to ISplitting/MSplitting positions to track character at split entry
    • Prevents spurious split entry by validating input character matches target's first character
    • Prioritizes phonetic splits (errors+0, fractional weight) over standard splits (errors+1)
    • Handles negative match_index in split completion when offset becomes very negative
  • New SubstitutionSet APIs

    • has_source(&self, source: &[u8]) -> bool: Check if source exists in restriction set
    • has_target_starting_with(&self, source: &[u8], first_char: char) -> bool: Validate target starts with given character
    • Comprehensive test coverage with 7 new unit tests
    • Supports both single-byte and multi-char storage architectures
  • New OperationType APIs

    • can_apply_to_source(&self, dict_chars: &[u8]) -> bool: Validate source without target for speculative split entry
    • matches_first_target_char(&self, dict_chars: &[u8], first_target_char: char) -> bool: Validate first character of split target
    • Full documentation with examples and theoretical justification for locality property
    • Enables generic phonetic split detection without hard-coding operation targets

Fixed

Phase 3b Bug Fixes (2025-11-14)

  • Entry Character Architecture Issue

    • Fixed: previous_input_char was shared at state level, causing incorrect character for parallel exploration paths
    • Solution: Store entry_char in each splitting position to track character read when entering that specific split
    • Impact: Enables correct double-split operations like "kat"→"chath" (k→ch, t→th)
  • Split Entry Priority Issue

    • Fixed: Both phonetic and standard splits were being entered simultaneously, exhausting error budget
    • Solution: Use if-else chain to prioritize phonetic splits (errors+0) over standard splits (errors+1)
    • Impact: Phonetic operations take precedence when both conditions are met
  • Split Entry Validation Issue

    • Fixed: Splits were entered speculatively without checking if input character matches target's first character
    • Solution: Validate with matches_first_target_char() before entering split state
    • Impact: Prevents entering t→th split when reading 'a' instead of 't'
  • I-Splitting Invariant Issue

    • Fixed: Standard invariant |offset| <= errors too restrictive for accumulated errors from other operations
    • Solution: Relaxed invariant for errors > 0 using subsumption-based constraints (errors >= -offset - n, offset >= -2*n)
    • Impact: Allows phonetic splits from positions with accumulated errors (e.g., after k→ch + insert 'a' + t→th)
  • Negative Match Index Handling

    • Fixed: When offset becomes very negative (< -n), match_index calculation wraps on usize cast
    • Solution: Check if match_index_i32 < 0 before casting, use full_word fallback for extraction
    • Impact: Prevents undefined behavior in word character extraction during split completion

Changed

Generalized Position Updates (2025-11-14)

  • Updated ISplitting and MSplitting position variants to include entry_char: char field
  • Modified subsumption logic to handle new entry_char field with pattern matching wildcards
  • Updated all position creation call sites in state transition functions
  • Enhanced position constructors (new_i_splitting, new_m_splitting) with entry_char parameter
  • All 4 new tests for splitting position constructors passing

Technical Details

Architecture Changes (2025-11-14)

  • Files Modified: 6 core files (substitution_set.rs, operation_type.rs, position.rs, state.rs, subsumption.rs, automaton.rs)
  • Test Coverage: 22/24 phonetic tests passing (91.7% success rate, up from 90.5%)
  • API Additions: 4 new public methods with full documentation
  • Test Additions: 11 new unit tests (7 for SubstitutionSet, 4 for positions)

Remaining Work (2025-11-14)

  • 2 failing tests: test_phonetic_split_multiple, test_phonetic_split_with_standard_ops
  • Issue: Word character extraction in edge cases when offset < -n
  • Root cause: Complex interaction between word_slice vs full_word extraction logic
  • Impact: Affects consecutive phonetic splits with accumulated errors

Performance

SubstitutionSet Optimizations (2025-11-12)

  • H1: Const Arrays for Presets - 15-28% faster initialization

    • Preset substitution sets now use compile-time const arrays
    • Eliminates runtime hash computations and char-to-byte conversions
    • Performance improvements:
      • phonetic_basic: 19.2% faster (196ns → 158ns)
      • keyboard_qwerty: 15.6% faster (587ns → 495ns)
      • leet_speak: 18.1% faster (245ns → 200ns)
      • ocr_friendly: 28.2% faster (224ns → 160ns)
    • Implementation: Direct byte insertion with pre-allocated capacity
    • Zero runtime overhead (compile-time optimization)
    • Documentation: docs/optimization/substitution-set/02-hypothesis1-const-arrays.md
  • H3: Hybrid Small/Large Strategy - 9-46% faster for small sets

    • Automatic strategy selection based on set size
    • Linear scan (Vec) for ≤4 pairs, hash lookup (FxHashSet) for >4 pairs
    • Crossover analysis validated 5-pair threshold empirically
    • Performance improvements (small sets):
      • 1 pair: 46.4% faster (376.7ns → 201.3ns, 1.87× speedup)
      • 2 pairs: 28.2% faster (366.8ns → 263.3ns, 1.39× speedup)
      • 3 pairs: 9.0% faster (363.6ns → 330.8ns, 1.10× speedup)
    • Integration test results: 21/25 improved (84%), zero critical regressions
    • Memory savings: 50-79% reduction for small sets (1-4 pairs)
    • Implementation: Enum-based hybrid with automatic upgrade at threshold
    • All 509 tests passing, production-ready
    • Documentation: docs/optimization/substitution-set/06-hypothesis3-hybrid.md
  • H2: Bitmap Optimization - Rejected

    • Evaluated 128×128 bit matrix for O(1) lookup
    • Results: 2.4× faster lookups but 4-13× slower initialization
    • Break-even point: ~690 lookups (typical queries have 50-300)
    • Decision: Rejected due to initialization cost outweighing lookup benefits
    • Lesson learned: Optimize full lifecycle, not just hot path
    • Documentation: docs/optimization/substitution-set/03-hypothesis2-bitmap.md
  • Complete optimization summary

    • Scientific methodology: Hypothesis-driven with rigorous benchmarking
    • Two production-ready optimizations (H1, H3)
    • Zero regressions in integration tests
    • Comprehensive documentation: docs/optimization/substitution-set/07-final-summary.md

Deprecated

OptimizedDawg (2025-11-11)

  • OptimizedDawg deprecated in favor of DynamicDawg
    • Comprehensive benchmarking revealed OptimizedDawg is 5-12× slower than DynamicDawg across all scales:
      • 1K words: 11.5× slower (16.1ms vs 1.40ms)
      • 10K words: 5.5× slower (307ms vs 55.5ms)
      • 32K words: 5.7× slower (781ms vs 137ms)
      • 100K words: 6.2× slower (2,555ms vs 409ms)
    • Missing critical features not available in OptimizedDawg:
      • MappedDictionary trait (no value storage support)
      • ValuedDictZipper trait (no hierarchical navigation)
      • Runtime mutations (no insert/remove operations)
      • Bloom filter optimization
      • Suffix caching
    • Analysis showed no Double-Array Trie features despite original hypothesis
    • Arena-based edge storage incompatible with DynamicDawg's mutability (cannot merge implementations)
    • Performance regression detected: OptimizedDawg showing 2-4% degradation while DynamicDawg shows 17-18% improvement
    • Migration: Simple drop-in replacement - change OptimizedDawg::from_terms() to DynamicDawg::from_terms()
    • Comprehensive deprecation notice: docs/deprecations/OPTIMIZED_DAWG_DEPRECATION.md
    • Backward compatibility maintained: Type remains available with deprecation warnings
    • Removed from default benchmark suite to reduce CI time

Changed

Phase 6: Dictionary Layer Completeness (2025-11-11)

  • Phase 6 is now 100% complete 🎉
    • All 9 production-ready dictionary backends support complete feature set
    • MappedDictionary support: 8/8 backends (100%)
      • PathMapDictionary, PathMapDictionaryChar
      • DynamicDawg, DynamicDawgChar
      • DoubleArrayTrie, DoubleArrayTrieChar
      • SuffixAutomaton, SuffixAutomatonChar
    • ValuedDictZipper support: 7/7 backends (100%)
      • PathMapZipper
      • DoubleArrayTrieZipper, DoubleArrayTrieCharZipper
      • DynamicDawgZipper, DynamicDawgCharZipper
      • SuffixAutomatonZipper, SuffixAutomatonCharZipper
    • OptimizedDawg excluded from counts as deprecated
    • Updated implementation status: docs/implementation-status/phase-6-dictionary-layer-completeness.md

Added

Multi-Backend Contextual Completion Support (2025-11-05)

  • DynamicContextualCompletionEngine with multiple dictionary backends

    • Renamed ContextualCompletionEngine to DynamicContextualCompletionEngine for clarity
    • Added deprecated type alias ContextualCompletionEngine for backward compatibility (will be removed in 1.0.0)
    • Extended support to DynamicDawg and DynamicDawgChar backends (in addition to PathMapDictionary)
    • Generic over D: MutableMappedDictionary<Value = Vec<ContextId>>
    • Convenience constructors: with_pathmap(), with_pathmap_char(), with_dynamic_dawg(), with_dynamic_dawg_char()
    • Performance benefit: DynamicDawg provides ~2.8x faster queries than PathMapDictionary
  • StaticContextualCompletionEngine for read-only dictionaries

    • New engine optimized for pre-built, immutable dictionaries
    • Supports DoubleArrayTrie and DoubleArrayTrieChar backends
    • Fastest query performance: ~12-16µs at distance 1 (compared to ~45µs for PathMap)
    • Finalized terms stored in separate HashMap instead of mutating dictionary
    • Query fusion architecture: merges results from static dictionary + finalized_terms + drafts
    • Generic over D: MappedDictionary<Value = Vec<ContextId>>
    • Convenience constructors: with_double_array_trie(), with_double_array_trie_char()
    • Ideal for LSP servers with large pre-built standard library dictionaries
  • Comprehensive Unicode support across all backends

    • Both engines support byte-level (u8) and character-level (char) dictionary variants
    • Correct Unicode edit distances for multi-byte UTF-8 sequences
    • PathMapDictionary + PathMapDictionaryChar (mutable, flexible)
    • DynamicDawg + DynamicDawgChar (mutable, faster queries)
    • DoubleArrayTrie + DoubleArrayTrieChar (immutable, fastest queries)

Changed

  • Contextual completion API evolution
    • ContextualCompletionEngine is now a deprecated type alias
    • Users should migrate to DynamicContextualCompletionEngine for clarity
    • No breaking changes: existing code continues to work with deprecation warning
    • Clear migration path documented in deprecation notice

0.6.0 - 2025-11-04

Added

SuffixAutomatonChar - Unicode Substring Matching (2025-11-04)

  • New SuffixAutomatonChar dictionary backend

    • Character-level variant of SuffixAutomaton for correct Unicode substring matching
    • Operates on Unicode scalar values (char) instead of bytes (u8)
    • Correct character-level matching for multi-byte UTF-8 sequences
    • Example: finds "café" as substring in "local café shop" with correct distances
    • Supports all Unicode: accented characters, CJK, emoji, Cyrillic, etc.
  • Full suffix automaton capabilities with Unicode

    • Thread-safe insert and remove operations
    • Online construction algorithm (O(n) amortized)
    • Endpos equivalence and suffix links
    • Generic over value types: SuffixAutomatonChar<V: DictionaryValue = ()>
    • Serialization support with proper bounds
  • Performance characteristics

    • ~5-8% slower than byte-level due to character iteration
    • ~4x memory for edge labels (4 bytes per char vs 1 byte per u8)
    • ≤2n-1 states for n-character text (same as byte-level)
    • Recommended for Unicode substring search applications
  • Comprehensive testing and documentation

    • 20 tests covering Unicode scenarios (café, emoji, CJK, mixed)
    • Module documentation with usage examples
    • Added to DOCUMENTATION_INDEX.md
    • Updated dictionary comparison tables

Zipper Implementations for Navigation (2025-11-04)

  • DynamicDawgZipper - Byte-level DAWG navigation

    • State-index-based navigation with lock-per-operation pattern
    • Implements DictZipper and ValuedDictZipper traits
    • Thread-safe concurrent access
    • 12 tests covering navigation, values, concurrency
  • DynamicDawgCharZipper - Character-level DAWG navigation

    • Unicode-aware zipper for DynamicDawgChar
    • Path tracking with Vec<char>
    • 14 tests including Unicode-specific scenarios
  • SuffixAutomatonZipper - Byte-level substring navigation

    • Efficient navigation through suffix automaton states
    • Lock-per-operation for minimal contention
    • 12 tests for substring matching scenarios
  • SuffixAutomatonCharZipper - Unicode substring navigation

    • Character-level zipper for SuffixAutomatonChar
    • Correct Unicode path tracking
    • 14 tests including emoji and CJK navigation

MappedDictionary Support for SuffixAutomaton (2025-11-04)

  • Extended SuffixAutomaton with value support

    • Made generic over V: DictionaryValue (default ())
    • Implemented MappedDictionary and MappedDictionaryNode traits
    • Added insert_with_value() and get_value() methods
    • Full backward compatibility with existing code
    • Proper serde serialization bounds
  • Use cases

    • Code search with metadata (file paths, line numbers)
    • Document search with occurrence positions
    • Log analysis with contextual information

Fixed

  • Serialization bounds for DoubleArrayTrieChar

    • Added serde bounds for generic type parameter V
    • Fixes compilation with --all-features flag
    • Applied to both DATSharedChar and DoubleArrayTrieChar structs
  • Type annotations in examples and tests

    • Updated examples to use explicit type parameters (SuffixAutomaton::<()>)
    • Fixed serialization test type annotations
    • Removed deprecated compressed_suffix_demo.rs example
  • Import paths in SuffixAutomatonChar doctests

    • Fixed module imports from suffix_automaton:: to suffix_automaton_char::
    • All 10+ doctests now compile correctly

Documentation

  • Updated src/dictionary/mod.rs

    • Added SuffixAutomatonChar to quick start guide
    • Updated comparison table with Unicode substring search
    • Added usage example with multi-language text
  • Updated DOCUMENTATION_INDEX.md

    • Added SuffixAutomatonChar to dictionary types table
    • Added 4 new zipper types to zipper section
    • Added SuffixAutomatonChar implementation details (~1100 lines)

Removed

  • CompressedSuffixAutomaton (experimental, incomplete)
    • Removed implementation file: src/dictionary/compressed_suffix_automaton.rs
    • Removed from prelude exports
    • Removed from module declarations
    • Removed from README.md
    • Breaking change: Code using CompressedSuffixAutomaton should migrate to:
      • SuffixAutomaton for byte-level substring matching
      • SuffixAutomatonChar for Unicode substring matching
    • Rationale: Was experimental, incomplete, and single-text only; superseded by fully-featured suffix automaton implementations

0.5.0 - 2025-11-04

Added

DynamicDawgChar - Unicode Support for Dynamic DAWG (2025-11-04)

  • New DynamicDawgChar dictionary backend

    • Character-level variant of DynamicDawg for correct Unicode Levenshtein distances
    • Operates on Unicode scalar values (char) instead of bytes (u8)
    • Correct character-level distances for multi-byte UTF-8 sequences
    • Example: "" → "¡" = distance 1 (not 2 bytes), "café" → "cafe" = distance 1 (not 2)
    • Supports all Unicode: accented characters, CJK, emoji, Cyrillic, etc.
  • Full dynamic operations with Unicode

    • Thread-safe insert and remove operations (same as DynamicDawg)
    • Compaction to restore minimality after removals
    • Generic over value types: DynamicDawgChar<V: DictionaryValue = ()>
    • Bloom filter and auto-minimization support
  • Performance characteristics

    • ~5-10% slower than byte-level due to UTF-8 decoding
    • ~4x memory for edge labels (4 bytes per char vs 1 byte per u8)
    • Significantly better fuzzy matching performance than PathMapChar
    • Recommended for Unicode applications requiring dynamic updates
  • Comprehensive testing and documentation

    • 28 new tests in tests/test_dynamic_dawg_char.rs covering Unicode scenarios
    • Tests for accented characters, CJK, emoji, transposition, value mapping
    • New example: examples/dynamic_dawg_unicode.rs demonstrating Unicode handling
    • Added to serialization tests (bincode and JSON round-trip)
    • Updated README.md with DynamicDawgChar recommendations
    • Updated src/dictionary/mod.rs documentation with comparison table
  • Use cases

    • Multi-language applications (any non-ASCII text)
    • Dynamic dictionaries with Unicode terms
    • Code completion for international programming
    • Spell checkers for non-English languages
    • Any application requiring correct Unicode edit distances with runtime updates

Generic DynamicDawg with Value Support (2025-11-04)

  • Made DynamicDawg generic over value types

    • Changed from DynamicDawg to DynamicDawg<V: DictionaryValue = ()> with default type parameter
    • Added value: Option<V> field to DawgNode for storing associated values
    • Implemented insert_with_value() and get_value() methods
    • Full backward compatibility: existing code using DynamicDawg continues to work
    • Enables fuzzy dictionaries with metadata (frequencies, scores, context IDs, etc.)
  • New MutableMappedDictionary trait

    • Extends MappedDictionary with insert_with_value() method
    • Implemented for DynamicDawg, PathMapDictionary, and PathMapDictionaryChar
    • Provides unified API for mutable dictionaries with values
    • Enables generic programming over different dictionary backends
  • Generic ContextualCompletionEngine

    • Made generic over D: MutableMappedDictionary<Value = Vec<ContextId>>
    • Can now use any mutable mapped dictionary backend (PathMap, DynamicDawg, etc.)
    • Convenience constructors maintain backward compatibility
    • with_dictionary() constructor for custom backends
    • All 93 contextual engine tests pass with generic implementation
  • Comprehensive integration tests

    • 19 new integration tests in tests/dynamic_dawg_integration.rs
    • Tests DynamicDawg with FuzzyMultiMap (6 tests)
    • Tests DynamicDawg with eviction wrappers: Lru, Lfu, Ttl, Age (9 tests)
    • Tests DynamicDawg with ContextualCompletionEngine (4 tests)
    • Validates end-to-end workflows with value aggregation and caching

Fixed

DynamicDawg Insert Bug (2025-11-04)

  • Critical bug fix: Suffix sharing causing incorrect term acceptance

    • Fixed bug where inserting "j" into ["kb", "jb"] caused "k" to be marked as valid
    • Root cause: Phase 2.1 suffix sharing created shared entry nodes
    • When both 'j' and 'k' edges pointed to same node, marking it final affected both paths
    • Solution: Disabled Phase 2.1 suffix sharing optimization
    • Trade-off: ~20-40% higher memory usage (mitigated by periodic compaction)
    • Preserved suffix sharing methods for future optimization work
  • Bug discovery and verification

    • Found by property-based testing (proptest)
    • Created minimal reproducing test case in tests/debug_proptest_failure.rs
    • All 20 DynamicDawg unit tests pass
    • All 19 integration tests pass
    • All 22 comprehensive property tests pass
    • 168 tests pass with --all-features enabled

DynamicDawg Performance Optimizations (2025-11-03)

  • Bloom Filter for fast negative lookups (88-93% improvement)

    • Probabilistic data structure with 3 hash functions and 10 bits per element
    • Accelerates contains() operations by rejecting non-existent terms early
    • Zero false negatives, <1% false positive rate with default configuration
    • Configurable via with_config() API: DynamicDawg::with_config(f32::INFINITY, Some(10000))
    • Benchmarks: contains() operations improved from ~38µs to ~3µs (10-12x faster)
    • Minimal memory overhead: ~1.25 bytes per term
  • Lazy Auto-Minimization (30% improvement for large datasets)

    • Automatic minimize() triggering based on configurable growth threshold
    • Default: disabled (threshold = f32::INFINITY), opt-in via with_config()
    • Configurable threshold: DynamicDawg::with_config(1.5, None) minimizes at 50% growth
    • Benchmark results: 30% faster insertions for 1000+ term datasets
    • Prevents unbounded memory growth during bulk insertions
    • Trade-off: adds ~5-10% overhead for small datasets (<100 terms)
  • Sorted Batch Insertion (4-8% improvement)

    • from_terms() now pre-sorts input before insertion
    • Better prefix/suffix sharing leads to more compact DAWG structure
    • Benchmark results: 4-8% faster construction for typical workloads
    • No API changes required - optimization is transparent
  • Comprehensive optimization analysis

    • Evaluated 7 optimization candidates with scientific methodology
    • 3 optimizations implemented and kept (sorted insertion, auto-minimize, Bloom filter)
    • 1 optimization rejected after analysis: RCU/Atomic Swapping (-1400% write regression)
    • 3 optimizations skipped with rationale: LRU suffix cache (low ROI), Adaptive edge storage (SmallVec sufficient), Incremental compaction (minimize() already provides this)
    • Full documentation: docs/optimizations/all_optimizations_final_report.md
  • New benchmarks for optimization validation

    • benches/auto_minimize_benchmark.rs - Auto-minimization threshold tuning
    • benches/bloom_filter_benchmark.rs - Bloom filter performance analysis
    • benches/compact_benchmark.rs - Compaction strategy comparison
  • Documentation

    • docs/optimizations/all_optimizations_final_report.md - Comprehensive optimization results (7 candidates analyzed)
    • docs/optimizations/rcu_assessment.md - Detailed RCU trade-off analysis
    • docs/optimizations/dynamic_dawg_optimization_results.md - Benchmark data and decision log

Contextual Code Completion Engine (2025-11-03)

  • Hierarchical scope-aware code completion with zipper-based navigation

    • Complete 6-phase implementation (Phases 1-6) as documented in roadmap
    • Character-level draft state management with incremental insertion
    • Checkpoint-based undo/redo for editor integration
    • Hierarchical context tree for lexical scope visibility (global → module → function → block)
    • Thread-safe concurrent queries and modifications (Arc/RwLock-based)
    • Mixed queries searching both finalized terms and active drafts simultaneously
  • Zipper architecture for efficient dictionary traversal

    • DictZipper and ValuedDictZipper trait abstractions (src/dictionary/zipper.rs)
    • PathMapZipper implementation with lock-per-operation pattern
    • AutomatonZipper for Levenshtein automaton state tracking
    • IntersectionZipper composing dictionary and automaton navigation
    • ZipperQueryIterator with BFS-based traversal and StatePool reuse
  • ContextualCompletionEngine API (src/contextual/)

    • create_root_context() / create_child_context() - Hierarchical scope creation
    • insert_char() / insert_str() - Incremental draft building (~4 µs per char)
    • checkpoint() / undo() - State management for editor undo/redo (~116 ns per checkpoint)
    • finalize() / finalize_direct() - Promote drafts to permanent dictionary terms
    • complete() - Fuzzy query with hierarchical visibility filtering
    • discard() / rollback_char() - Draft manipulation
  • Value-filtered queries for scoped completions

    • query_filtered() - Custom predicate-based filtering during traversal
    • query_by_value_set() - Efficient set-based scope filtering
    • Significantly faster than post-filtering results (filtering during traversal)
  • Performance characteristics

    • Insert character: ~4 µs (12M chars/sec throughput)
    • Checkpoint creation: ~116 ns per operation
    • Query (500 terms, distance 1): ~11.5 µs
    • Query (500 terms, distance 2): ~309 µs
    • Thread-safe with fine-grained locking (DashMap for drafts, RwLock for dictionary)
  • Comprehensive test coverage

    • 10 PathMapZipper tests (navigation, finality, values, cloning)
    • 11 AutomatonZipper tests (state transitions, all algorithm variants)
    • 9 IntersectionZipper tests (match detection, distance computation)
    • 7 ZipperQueryIterator tests (lazy evaluation, early termination)
    • Draft lifecycle integration tests (insert → checkpoint → rollback → restore → finalize)
    • Contextual stress tests (concurrent operations, large-scale scenarios)
  • Benchmarks and performance analysis

    • benches/contextual_completion_benchmarks.rs - Single-threaded performance
    • benches/concurrent_completion_benchmarks.rs - Concurrency benchmarks
    • benches/zipper_vs_node_benchmark.rs - Comparison with node-based queries
    • Zipper-based queries are 1.66-1.97× slower than node-based (acceptable trade-off for architectural benefits)
  • Documentation

    • docs/design/contextual-completion-api.md - Complete API specification (906 lines)
    • docs/design/contextual-completion-roadmap.md - 6-phase implementation plan (490 lines)
    • docs/design/contextual-completion-zipper.md - Architecture design (745 lines)
    • docs/design/contextual-completion-progress.md - Implementation tracking and status
    • docs/design/zipper-vs-node-performance.md - Performance analysis and trade-offs
    • Updated README.md with contextual completion examples and zipper API usage
  • Example code

    • examples/contextual_completion.rs - Complete demonstration (221 lines)
      • Hierarchical scope creation (global → function → block)
      • Incremental typing simulation
      • Checkpoint/undo workflows
      • Draft finalization
      • Visibility scoping
  • Use Cases

    • LSP servers with multi-file scope awareness
    • Code editors with context-sensitive completion
    • REPL environments with session-scoped symbols
    • Any application requiring hierarchical fuzzy matching with dynamic state
  • Performance Notes

    • Sub-millisecond response times for interactive use
    • Zipper overhead acceptable for contextual use cases (1.66-1.97× vs node-based)
    • Thread-safe: share engine across threads with Arc
    • Memory: ~1KB overhead per active context (within design targets)

UTF-8 Optimization Documentation (2025-11-04)

  • Comprehensive UTF-8 performance analysis
    • Documented current state of UTF-8/Unicode optimization in docs/optimization/UTF8_OPTIMIZATION_STATUS.md
    • Identified ~5-10% UTF-8 overhead as inherent to character-level operations (acceptable trade-off)
    • Catalogued already-optimized components: SIMD distance computation (20-64% gains), arena allocation, state pooling, adaptive search
    • Ranked top 3 optimization opportunities by impact and risk:
      1. Fix DynamicDawgChar suffix sharing bug (20-40% memory savings, HIGH RISK)
      2. PathMapChar batch validation (5-10% speedup, LOW RISK)
      3. SSE4.1 fallback (1.5-2x on older CPUs, LOW RISK)
    • Updated docs/optimization/README.md index with UTF-8 section and reading guides
    • Recommendation: Focus on correctness over micro-optimization given diminishing returns

Fixed

Test Compilation (2025-11-04)

  • Fixed feature-gated test compilation error
    • Added #[cfg(feature = "pathmap-backend")] to test_dynamic_dawg_char_value_filtered_query() in tests/test_dynamic_dawg_char.rs
    • Test uses FuzzyMultiMap from cache module which requires pathmap-backend feature
    • Ensures tests compile successfully both with and without optional features
    • Resolves: error[E0433]: failed to resolve: could not find 'cache' in 'liblevenshtein'

GitHub Actions Workflow (2025-11-04)

  • Fixed crates.io publishing workflow failure
    • Added sed command to convert pathmap-backend = ["pathmap"] to empty marker feature pathmap-backend = []
    • Release workflow comments out PathMap git dependency for crates.io compatibility
    • After commenting dependency, feature definition must also be updated to avoid Cargo validation error
    • Resolves: feature 'pathmap-backend' includes 'pathmap' which is neither a dependency nor another feature
    • File: .github/workflows/release.yml line 454-456

Code Quality (2025-11-04)

  • Resolved all clippy warnings with -D warnings enabled
    • Fixed multiple_bound_locations: Removed duplicate D: Dictionary bound (src/cli/commands.rs:689)
    • Fixed unused_imports: Removed unused Dictionary import (src/contextual/engine.rs:13)
    • Fixed should_implement_trait: Renamed DraftBuffer::from_str() to from_string() to avoid confusion with std::str::FromStr::from_str() (src/contextual/draft_buffer.rs:107)
    • Fixed filter_next: Replaced .filter().next() with .find() (src/dictionary/pathmap_char.rs:432)
    • Fixed needless_range_loop (4 instances): Converted index-based loops to idiomatic iterator patterns with enumerate() (src/transducer/simd.rs:150, 400, 461, 861)
    • All 168 tests pass with strict clippy checks

0.4.0 - 2025-10-31

Added

Unicode Support (2025-10-30)

  • Character-level dictionary variants for correct Unicode Levenshtein distances

    • DoubleArrayTrieChar - Character-level Double-Array Trie implementation
    • PathMapDictionaryChar - Character-level PathMap with dynamic updates (requires pathmap-backend feature)
    • Proper handling of multi-byte UTF-8 sequences (accented characters, CJK, emoji)
    • Generic CharUnit trait abstraction over u8 (byte-level) and char (character-level)
    • ~5% performance overhead for UTF-8 decoding, 4x memory for edge labels (char vs u8)
  • Comprehensive Unicode test coverage

    • 19 PathMapChar integration tests (all passing)
    • Tests for emoji (4-byte UTF-8), CJK (3-byte UTF-8), accented characters (2-byte UTF-8)
    • Empty query, exact match, one-edit distance, transposition, various distance levels
    • Dynamic operations (insert/remove), value mapping, value filtering
    • Edge cases (empty dictionary, single characters, normalization)
  • Fixed core Unicode issue: "" → "¡" now correctly requires distance 1 (one character) instead of distance 2 (two bytes)

  • Updated cache eviction nodes

    • All 8 cache wrapper nodes support generic Unit type
    • Noop, LRU, LRU Optimized, LFU, TTL, Age, Cost-Aware, Memory Pressure
  • Documentation

    • Updated README.md with Unicode support section and examples
    • Character-level backends in dictionary comparison table
    • Guidance on when to use byte-level vs character-level variants
    • UTF8_IMPLEMENTATION.md - Complete technical design document (300+ lines)
    • UTF8_IMPLEMENTATION_STATUS.md - Implementation status report (250+ lines)

Phase 4: SIMD Optimization

  • Comprehensive SIMD acceleration across critical performance paths

    • 8 SIMD-optimized components with 20-64% real-world performance gains
    • ~2,300 lines of optimized SIMD code with runtime CPU feature detection
    • Data-driven threshold tuning based on empirical benchmarking
    • Extensive documentation (950+ lines across 3 analysis documents)
  • Batch 1: SSE4.1 fallback + SIMD affix stripping

    • Runtime CPU feature detection (is_x86_feature_detected!)
    • SSE4.1 fallback paths for all AVX2 operations
    • SIMD-accelerated prefix/suffix stripping for string comparisons
  • Batch 2A: Transducer state operations

    • Characteristic vector SIMD (2-3x faster for window sizes ≥8)
    • Position subsumption SIMD (1.5-2x faster for batch operations)
    • State minimum distance SIMD (2x faster for states with 8+ positions)
    • Integrated into State::min_distance() and transducer transitions
  • Batch 2B: Dictionary edge lookup SIMD (commit: 89cb3b8, 488707b, 337fd83)

    • Generic SIMD implementation supporting both usize and u32 targets
    • SSE4.1 implementation: 16-way byte comparison
    • Data-driven threshold optimization: scalar <12 edges, SSE4.1 12-16 edges
    • Performance impact (after threshold optimization):
      • Realistic workload: 43% faster (21.9ns → 38.9ns)
      • Overall queries: 20% faster (36.4µs → 45.9µs)
      • Distance-1 queries: 5% faster (2.55µs → 2.69µs)
      • Distance-2 queries: 6% faster (9.19µs → 9.75µs)
      • Small edge lookups (4 edges): 64% faster (3.54ns → 10.03ns)
    • Integrated into DAWG and Optimized DAWG dictionaries
  • Batch 3: Distance matrix SIMD (pre-existing)

    • AVX2 implementation: 8 u32 values in parallel
    • SSE4.1 implementation: 4 u32 values in parallel
    • Automatic dispatch with threshold-based selection
    • Integrated into distance::standard_distance() when SIMD feature enabled
  • Comprehensive test coverage

    • 193 total tests passing with SIMD enabled
    • 14 edge lookup-specific tests with boundary conditions
    • SIMD vs scalar validation for all critical paths
    • Integration tests for DAWG, transducer, and query operations
  • Documentation

    • docs/PHASE4_SIMD_COMPLETION_STATUS.md - Overall completion summary (350+ lines)
    • docs/BATCH2A_INTEGRATION_ANALYSIS.md - State operations analysis
    • docs/BATCH2B_PERFORMANCE_ANALYSIS.md - Edge lookup detailed analysis (450+ lines)

Query Iterator Optimization (2025-10-29)

  • Comprehensive query iterator testing and optimization

    • Fixed 2 critical bugs in ordered query iterator (result dropping, lexicographic ordering)
    • Added 20 new comprehensive tests covering distances 0-99 and edge cases
    • Created 20 benchmarks for performance analysis (criterion + flamegraph profiling)
    • All 139 tests passing with full coverage of query modifiers
  • Adaptive sorting optimization

    • Insertion sort for small buffers (≤10 items) for better cache locality
    • Unstable sort for larger buffers (~20-30% faster)
    • Pre-sized buffer allocation to reduce reallocations
    • Performance improvements: 0.7% faster for distance 1 (common case), up to 30% faster for distance 3+
  • Query iterator benchmarks (benches/query_iterator_benchmarks.rs, benches/query_profiling.rs)

    • 10 criterion benchmarks covering various query scenarios
    • 10 flamegraph-optimized profiling benchmarks
    • Distance scaling, dictionary size scaling, algorithm comparison
    • Early termination efficiency testing

Changed

Documentation Reorganization - Phase 2 (2025-10-29)

  • Analysis documentation moved to docs/analysis/

    • Created docs/analysis/fuzzy-maps/ - 7-phase optimization journey (01-07)
    • Created docs/analysis/hierarchical-scope/ - Design and benchmark analysis
    • Moved 10 analysis files from project root to organized structure
    • Added comprehensive index files (00_README.md, README.md) for navigation
    • 58% reduction in root directory clutter (17 → 7 markdown files)
  • Documentation structure improvements

    • docs/analysis/fuzzy-maps/ - Complete fuzzy maps optimization story (-7.1% → +5.8%)
    • docs/analysis/hierarchical-scope/ - Scope completion design and results
    • docs/guides/HIERARCHICAL_SCOPE_COMPLETION.md - User-facing guide
    • Updated docs/README.md with new "Analysis & Research" section
    • Fixed broken links after file moves
    • Updated .gitignore with LaTeX artifact patterns

Documentation Reorganization - Phase 1 (2025-10-29)

  • Optimization documentation moved to docs/optimization/

    • Created organized structure with README.md as entry point
    • 14 optimization documents now properly organized
    • Removed 5 duplicate/obsolete documentation files (~57KB cleanup)
    • Project root now clean with only essential documentation
  • Documentation consolidation

    • docs/optimization/README.md - Main optimization documentation index
    • Query optimization documents (COMPLETE, WORK_SUMMARY, PERFORMANCE_ANALYSIS, FLAMEGRAPH_ANALYSIS)
    • Component optimization reports (STATE_OPERATIONS, TRANSITION, SUBSUMPTION, POOL_INTERSECTION)
    • Analysis documents organized by component

Fixed

Query Iterator Bug Fixes (2025-10-29)

  • Bug #1: Large distance queries dropping results (src/transducer/ordered_query.rs:126-197)

    • Query "quuo" with distance 99 only returned 2 of 5 terms
    • Fixed with distance bucket re-queuing logic
    • Regression test added in tests/large_distance_test.rs
  • Bug #2: Lexicographic ordering not maintained (src/transducer/ordered_query.rs:64-83, 126-197)

    • Results at same distance not lexicographically sorted
    • Fixed with sorted_buffer and explicit sorting
    • Comprehensive tests added in tests/query_comprehensive_test.rs

0.3.0 - 2025-10-26

Added

  • Arch Linux package support (1199173)

    • .pkg.tar.zst packages for x86_64 and aarch64 architectures
    • packaging/arch/PKGBUILD with architecture-specific RUSTFLAGS
    • Automated building and testing in CI using Docker with archlinux:latest
    • Sanity tests verify installation and basic functionality
  • RPM package support (1199173)

    • .rpm packages for RedHat, Fedora, CentOS distributions
    • RPM metadata in Cargo.toml using cargo-generate-rpm
    • Automated building and testing in Fedora 40 container
    • Proper library paths for /usr/lib64

Changed

  • CI workflow improvements (1cd9189)
    • Use explicit CPU features (-C target-feature=+aes,+sse2 for x86_64, +aes,+neon for ARM64)
    • Replaced -C target-cpu=native to ensure gxhash dependency compatibility
    • Applied to nightly.yml and release.yml workflows

Fixed

  • Code quality improvements (0f29a30)

    • Fixed all 15 clippy warnings without suppressing any checks
    • Redundant pattern matching: if let Err(_) = ....is_err() (2 instances)
    • Identical if blocks: Simplified parse_limit logic
    • Borrowed box: &Box<T>&T (2 instances)
    • Needless range loops: Use iterator patterns with enumerate() (5 instances)
    • Method naming: Renamed from_iterfrom_terms to avoid FromIterator confusion (44 call sites)
    • Too many arguments: Refactored to use structs (2 functions)
  • Library naming corrections (1199173)

    • Fixed library names to use correct double-lib prefix:
      • libliblevenshtein.so (Linux shared library)
      • libliblevenshtein.rlib (Rust static library)
      • libliblevenshtein.dylib (macOS shared library)
    • Updated across all packaging files and CI workflows

Added

Development Infrastructure (2025-10-25)

  • Git hooks for preventing accidental commits (116d617)
    • Pre-commit hook checks for uncommented [patch] sections in Cargo.toml
    • Prevents committing local development overrides (e.g., local PathMap paths)
    • Installation script: ./scripts/install-git-hooks.sh
    • Clear error messages with fix suggestions
    • Documentation in .githooks/README.md

Changed

Dependency Management (2025-10-25)

  • PathMap dependency now uses GitHub repository (77e6b56)
    • Changed from local path to git = "https://github.com/Adam-Vandervorst/PathMap.git"
    • Added commented [patch] section for local development override
    • Removed PathMap checkout steps from GitHub Actions workflows (automatic fetch)
    • Created .cargo/config.toml.local-example for local dev setup
    • Updated CONTRIBUTING.md with instructions for both approaches
    • Benefits: cleaner CI/CD, easier for contributors, works from crates.io

Documentation (2025-10-25)

  • Comprehensive documentation restructuring (d9a52d0)
    • Created docs/README.md as central documentation index (177 lines)
    • Organized documentation into categories (Getting Started, User Guides, Developer Docs, Benchmarks)
    • Archived 20 historical benchmark files to docs/archive/benchmarks/
    • Updated FEATURES.md for v0.2.0 (DynamicDawg, OrderedQueryIterator, compression, protobuf)
    • Created comprehensive BUILD.md (434 lines) with build instructions
    • Updated CONTRIBUTING.md for v0.2.0 features and workflows
    • All docs now include version headers and last-updated dates

CI/CD (2025-10-25)

  • GitHub Actions workflow badges (5c5853a)

    • Added CI, Nightly Tests, Release, License, and Crates.io badges to README
  • Comprehensive GitHub Actions workflows (e065043)

    • ci.yml: Main CI with test matrix (Ubuntu + macOS, stable + nightly Rust)
    • release.yml: Multi-platform builds (Linux x86_64/ARM64, macOS x86_64/ARM64, .deb packages)
    • nightly.yml: Daily validation with code coverage, security audits, benchmark tracking
    • Total: 647 lines of workflow automation

0.2.0 - 2025-10-25

Added

Compression Support (2025-10-25)

  • Gzip compression for dictionary serialization (f8e23b6)

    • Generic GzipSerializer<S> wrapper for any serialization format
    • 85% file size reduction with ~1.6x deserialization overhead
    • New compression feature flag
    • Comprehensive benchmarks showing compression tradeoffs
  • CLI integration for compressed formats (519e183)

    • bincode-gz, json-gz, protobuf-gz format variants
    • Automatic file extension handling (.bin.gz, .json.gz, .pb.gz)
    • Seamless convert, query, and save operations with compressed dictionaries

Code Completion Features (2025-10-24)

  • Filtering and prefix matching (eea90dd)

    • Filter support for OrderedQueryIterator
    • Prefix matching mode for autocomplete scenarios
    • Real-world code completion examples
  • Contextual filtering optimizations (9c27575)

    • Bitmap-based context masking for instant context switching
    • Sub-trie construction for restricted search spaces
    • Examples: advanced_contextual_filtering.rs, contextual_filtering_optimization.rs
    • Comprehensive performance comparison (post-filtering vs pre-filtering)
  • Code completion guide (c3551ee)

    • Detailed documentation for implementing IDE-style autocomplete
    • Performance recommendations for different filtering strategies

OrderedQueryIterator (2025-10-23)

  • Distance-first, lexicographic ordering (319d4e8)

    • Results ordered by distance first, then alphabetically
    • Efficient heap-based implementation
    • Examples and benchmarks comparing to unordered queries
  • Index-based DAWG query iterator (56fc643)

    • Memory-efficient index-based state management for DAWGs
    • Eliminates need for cloning nodes during traversal

Dictionary Features (2025-10-22)

  • DynamicDawg with online modifications (ec76137)

    • Insert and delete operations on DAWG structures
    • Minimize/compaction support for optimal memory usage
    • Reference-counted node sharing for efficient mutations
  • DAWG and serialization support (4fc3c16)

    • Directed Acyclic Word Graph (DAWG) backend
    • Bincode, JSON, and Protobuf serialization
    • Builder pattern for dictionary construction
    • Full-featured CLI tool with REPL
  • Real-world dictionary validation (4a9ed37)

    • Benchmarks with system dictionaries (/usr/share/dict/words)
    • Validation against large real-world datasets

Performance Improvements

Filtering and Prefix Optimizations (2025-10-24)

  • Phase 3: Final optimizations (5c485a4)

    • Total improvements: 5-18% across all operations
    • Comprehensive benchmark suite for filtering/prefix scenarios
  • Phase 2: Aggressive inlining (5cd73f5)

    • Inlined hot path functions
    • Improved epsilon closure handling
  • Phase 1: Initial optimizations (90e1482)

    • Optimized filter predicate evaluation
    • Reduced allocation overhead in prefix mode

DAWG Performance (2025-10-22)

  • 3.3x speedup for DAWG operations (3f6bc58)

    • Major algorithmic improvements
    • Optimized node traversal
  • Lightweight PathNode optimization (9fc42b1)

    • Reduced memory footprint for query nodes
    • Faster node construction and copying

Core Engine Optimizations (2025-10-21)

  • Arc Path Sharing (9de7421)

    • Eliminated expensive cloning operations
    • Shared ownership for path tracking
  • StatePool allocation reuse (e375303)

    • Object pool pattern for state reuse
    • Exceptional performance improvements
  • SmallVec integration (44157d5)

    • Stack-allocated small vectors
    • Reduced heap allocation pressure
  • Lazy edge iteration (10ea210)

    • 15-50% faster PathMap edge iteration
    • Zero-copy iterator implementation

Documentation

Documentation Reorganization (2025-10-31)

  • Comprehensive documentation restructure for improved discoverability

    • Moved 16+ files from project root to organized docs/ subdirectories
    • Created intuitive directory structure: user-guide/, developer-guide/, design/, research/, bug-reports/, completion-reports/, implementation-status/, benchmarks/, archive/
    • Clean project root with only essential files (README, CHANGELOG, LICENSE, Cargo.toml, .gitignore)
  • 11 new README.md navigation indexes

    • Each documentation directory has comprehensive README with file descriptions and navigation
    • Clear entry points for users, contributors, and researchers
  • 4 new comprehensive user guides (10,000+ lines total)

    • getting-started.md - Installation, basic usage, backend/algorithm selection
    • algorithms.md - Deep dive into Standard, Transposition, and MergeAndSplit algorithms
    • backends.md - Complete backend comparison with performance characteristics
    • serialization.md - Save/load dictionaries with format comparison and best practices
  • Updated all cross-references and internal links

    • Fixed main README.md documentation section
    • Rewrote docs/README.md as comprehensive documentation index
    • Updated developer-guide references (CONTRIBUTING.md → contributing.md, BUILD.md → building.md)
    • Corrected all version numbers from v0.2.0/v0.3.0 → v0.4.0
  • Consolidated related documentation

    • 9 SIMD research files → research/simd-optimization/
    • Distance optimization docs → research/distance-optimization/
    • Bug analysis → bug-reports/
    • Historical docs → archive/ (benchmarks/, implementation/, optimization/, performance/)
  • Comprehensive optimization summary (b536a7a)

    • Detailed performance analysis
    • Benchmark results and methodology
  • Code completion guide (c3551ee)

    • IDE integration patterns
    • Performance best practices

Changed

  • Updated default serialization format to Protobuf when available
  • Improved error messages in CLI tool
  • Enhanced benchmark suite with real-world scenarios

Fixed

  • Eliminated State::clone overhead in hot paths
  • Fixed unused import warnings in example files
  • Corrected dead code warnings in demonstration code

0.1.0 - Initial Release

Added

  • Core Levenshtein automaton implementation
  • PathMap dictionary backend
  • Standard and transposition distance algorithms
  • Basic query functionality
  • Initial documentation and examples

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