cppcheck quality pass + V2 numerical framework removal — v3.5.0

CHANGELOG.md

@@ -7,6 +7,20 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [3.5.0] - 2026-05-06
+
+cppcheck quality pass and V2 numerical framework removal. 37/37 tests pass.
+
+### Removed
+
+- **V2 numerical safety framework** (`include/libhmm/math/numerical_stability.h`,
+  `src/common/numerical_stability.cpp`, `tests/common/test_numerical_stability.cpp`):
+  `NumericalSafety`, `ConvergenceDetector`, `AdaptivePrecision`, `ErrorRecovery`,
+  and `NumericalDiagnostics` were built for the pre-V3 scaled-calculator architecture
+  and had no callers since the log-space-only pivot in V3. cppcheck confirmed every
+  method was unreachable; dead callee chain back to the deleted scaled trainers.
+  Files and associated test removed. 37/38 → 37 tests.
+
 ## [3.4.0] - 2026-05-05
 
 Code quality refactoring (Phases 1–3) and JSON serialization. 38/38 tests pass.

CMakeLists.txt

@@ -58,7 +58,7 @@ if(APPLE AND NOT CMAKE_CXX_COMPILER)
 endif()
 
 project(libhmm
-    VERSION 3.4.0
+    VERSION 3.5.0
     DESCRIPTION "Modern C++20 Hidden Markov Model Library"
     LANGUAGES CXX
 )
@@ -518,7 +518,6 @@ set(LIBHMM_SOURCES
     src/hmm.cpp
     src/common/common.cpp
     src/common/string_tokenizer.cpp
-    src/common/numerical_stability.cpp
     src/common/weighted_stats.cpp
     src/performance/transcendental_kernels.cpp
     src/distributions/distribution_base.cpp

README.md

@@ -3,8 +3,8 @@
 [![C++20](https://img.shields.io/badge/C%2B%2B-20-blue.svg)](https://isocpp.org/std/the-standard)
 [![CMake](https://img.shields.io/badge/CMake-3.20%2B-blue.svg)](https://cmake.org/)
 [![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
-[![Version](https://img.shields.io/badge/Version-3.4.0-brightgreen.svg)](https://github.com/OldCrow/libhmm/releases)
-[![Tests](https://img.shields.io/badge/Tests-38%2F38_Passing-success.svg)](tests/)
+[![Version](https://img.shields.io/badge/Version-3.5.0-brightgreen.svg)](https://github.com/OldCrow/libhmm/releases)
+[![Tests](https://img.shields.io/badge/Tests-37%2F37_Passing-success.svg)](tests/)
 [![SIMD](https://img.shields.io/badge/SIMD-AVX--512%2FAVX2%2FSSE2%2FNEON-blue.svg)](src/distributions/)
 [![CI](https://github.com/OldCrow/libhmm/actions/workflows/ci.yml/badge.svg)](https://github.com/OldCrow/libhmm/actions)
 
@@ -148,7 +148,7 @@ libhmm/
 │   ├── training/      # Layer 4: BaumWelch, Viterbi, SegmentalKMeans
 │   └── io/            # JSON (hmm_json.h) + legacy XML I/O
 ├── src/               # Implementation (mirrors include/)
-├── tests/             # 38-test GTest suite
+├── tests/             # 37-test GTest suite
 ├── examples/          # 12 usage demonstrations
 ├── tools/             # simd_inspection, batch_performance, hmm_validator (.json/.xml)
 ├── samples/           # Reference HMM files (two_state_gaussian, casino) in JSON and XML

include/libhmm/distributions/beta_distribution.h

@@ -135,25 +135,6 @@ class BetaDistribution : public DistributionBase {
     void fit(std::span<const double> data, std::span<const double> weights) override;
     [[nodiscard]] bool isDiscrete() const noexcept override { return false; }
 
-    /**
-     * Vectorized batch computation of PDF for multiple values.
-     * Optimized for processing many values efficiently with cache reuse.
-     *
-     * @param values Vector of input values
-     * @param results Output vector for results (will be resized if needed)
-     */
-    void getProbabilityBatch(const std::vector<double> &values, std::vector<double> &results);
-
-    /**
-     * Vectorized batch computation of log PDF for multiple values.
-     * Optimized for processing many values efficiently with cache reuse.
-     *
-     * @param values Vector of input values
-     * @param results Output vector for results (will be resized if needed)
-     */
-    void getLogProbabilityBatch(const std::vector<double> &values,
-                                std::vector<double> &results) const;
-
     /**
      * Resets the distribution to default parameters (α = 1.0, β = 1.0).
      * This corresponds to a uniform distribution on [0,1].

include/libhmm/distributions/discrete_distribution.h

@@ -113,6 +113,19 @@ class DiscreteDistribution : public DistributionBase {
             throw std::invalid_argument("Probability value must be between 0 and 1");
     }
 
+    /// Fills pdf_ with uniform probabilities 1/numSymbols_ and invalidates the cache.
+    ///
+    /// This exists as a private non-virtual helper so the constructor can
+    /// perform the same initialisation as reset() without invoking a virtual
+    /// function during construction (where virtual dispatch is not active and
+    /// cppcheck correctly flags the call as misleading). reset() delegates
+    /// here so the logic lives in exactly one place.
+    void init_uniform() noexcept {
+        const double p = 1.0 / static_cast<double>(numSymbols_);
+        std::fill(pdf_.begin(), pdf_.end(), p);
+        invalidateCache();
+    }
+
 public:
     /**
      * Constructs a Discrete distribution with given number of symbols.
@@ -124,7 +137,7 @@ class DiscreteDistribution : public DistributionBase {
     explicit DiscreteDistribution(int symbols = 10)
         : DistributionBase{}, numSymbols_{validateSymbols(symbols)}, pdf_(numSymbols_),
           cachedSum_{1.0}, cachedEntropy_{0.0} {
-        reset();
+        init_uniform();
     }
 
     DiscreteDistribution(const DiscreteDistribution &other) = default;

include/libhmm/distributions/distribution_base.h

@@ -25,7 +25,7 @@ class Reader;
  */
 class DistributionBase : public EmissionDistribution {
 public:
-    virtual ~DistributionBase() = default;
+    ~DistributionBase() override = default;
 
     DistributionBase();
     DistributionBase(const DistributionBase &other);

include/libhmm/distributions/gamma_distribution.h

@@ -89,7 +89,7 @@ class GammaDistribution : public DistributionBase {
      * Evaluates the LOWER INCOMPLETE gamma function at x
      * Uses numerical approximation for computational efficiency
      */
-    double ligamma(double a, double x) noexcept;
+    static double ligamma(double a, double x) noexcept;
 
 public:
     /**

include/libhmm/distributions/log_normal_distribution.h

@@ -65,7 +65,7 @@ class LogNormalDistribution : public DistributionBase {
      * @param stdDev Standard deviation of ln(X) (must be positive and finite)
      * @throws std::invalid_argument if parameters are invalid
      */
-    void validateParameters(double mean, double stdDev) const {
+    static void validateParameters(double mean, double stdDev) {
         if (std::isnan(mean) || std::isinf(mean)) {
             throw std::invalid_argument("Mean parameter must be a finite number");
         }

include/libhmm/distributions/negative_binomial_distribution.h

@@ -64,7 +64,7 @@ class NegativeBinomialDistribution : public DistributionBase {
      * @param p Success probability (must be in (0,1])
      * @throws std::invalid_argument if parameters are invalid
      */
-    void validateParameters(double r, double p) const {
+    static void validateParameters(double r, double p) {
         if (std::isnan(r) || std::isinf(r) || r <= 0.0) {
             throw std::invalid_argument("Number of successes must be positive");
         }
@@ -247,7 +247,7 @@ class NegativeBinomialDistribution : public DistributionBase {
      * @param value The value at which to evaluate the CDF
      * @return Cumulative probability P(X ≤ value)
      */
-    [[nodiscard]] double CDF(double value) const noexcept;
+    [[nodiscard]] double getCumulativeProbability(double value) const noexcept;
 
     /**
      * Gets the mode of the distribution.

include/libhmm/distributions/pareto_distribution.h

@@ -88,7 +88,7 @@ class ParetoDistribution : public DistributionBase {
      * @param xm Scale parameter (must be positive and finite)
      * @throws std::invalid_argument if parameters are invalid
      */
-    void validateParameters(double k, double xm) const {
+    static void validateParameters(double k, double xm) {
         if (std::isnan(k) || std::isinf(k) || k <= 0.0) {
             throw std::invalid_argument("Shape parameter k must be a positive finite number");
         }

include/libhmm/distributions/poisson_distribution.h

@@ -73,7 +73,7 @@ class PoissonDistribution : public DistributionBase {
      * @param k Value to validate
      * @return true if k is a valid count, false otherwise
      */
-    bool isValidCount(double k) const noexcept {
+    static bool isValidCount(double k) noexcept {
         return k >= 0.0 && std::floor(k) == k && std::isfinite(k);
     }
 

include/libhmm/distributions/weibull_distribution.h

@@ -83,7 +83,7 @@ class WeibullDistribution : public DistributionBase {
      * @param lambda Scale parameter (must be positive and finite)
      * @throws std::invalid_argument if parameters are invalid
      */
-    void validateParameters(double k, double lambda) const {
+    static void validateParameters(double k, double lambda) {
         if (std::isnan(k) || std::isinf(k) || k <= 0.0) {
             throw std::invalid_argument("Shape parameter k must be a positive finite number");
         }

include/libhmm/io/xml_file_reader.h

@@ -76,7 +76,7 @@ class XMLFileReader {
      * @return Loaded HMM object
      * @throws std::runtime_error if deserialization fails
      */
-    Hmm readFromStream(std::ifstream &stream);
+    static Hmm readFromStream(std::ifstream &stream);
 };
 
 } // namespace libhmm

include/libhmm/io/xml_file_writer.h

@@ -68,7 +68,7 @@ class XMLFileWriter {
      * @param stream Output stream
      * @throws std::runtime_error if serialization fails
      */
-    void writeToStream(const Hmm &hmm, std::ofstream &stream);
+    static void writeToStream(const Hmm &hmm, std::ofstream &stream);
 };
 
 } // namespace libhmm

include/libhmm/linalg/basic_matrix.h

@@ -341,11 +341,11 @@ class BasicMatrix {
     BasicVector<T> row_sums() const {
         BasicVector<T> result(rows_);
         for (size_type i = 0; i < rows_; ++i) {
-            T sum = T{};
+            T row_sum = T{};
             for (size_type j = 0; j < cols_; ++j) {
-                sum += (*this)(i, j);
+                row_sum += (*this)(i, j);
             }
-            result[i] = sum;
+            result[i] = row_sum;
         }
         return result;
     }
@@ -357,11 +357,11 @@ class BasicMatrix {
     BasicVector<T> column_sums() const {
         BasicVector<T> result(cols_);
         for (size_type j = 0; j < cols_; ++j) {
-            T sum = T{};
+            T col_sum = T{};
             for (size_type i = 0; i < rows_; ++i) {
-                sum += (*this)(i, j);
+                col_sum += (*this)(i, j);
             }
-            result[j] = sum;
+            result[j] = col_sum;
         }
         return result;
     }