llm toolingHEADmaster

1 files changed, 158 insertions, 0 deletions

diff --git a/tests/test_genetic.c b/tests/test_genetic.c
new file mode 100644
index 0000000..e7bb55b
--- /dev/null
+++ b/tests/test_genetic.c
@@ -0,0 +1,158 @@
+// Tests for genetic.h - genetic algorithm generation step
+typedef char *ga_individual_t;
+#define GENETIC_IMPLEMENTATION
+#include "../include/genetic.h"
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include <time.h>
+#include <float.h>
+
+#define ASSERT(cond, msg)                                                        \
+  do {                                                                           \
+    if (!(cond)) {                                                               \
+      fprintf(stderr, "FAIL: %s (test_genetic.c:%d)\n", msg, __LINE__);         \
+      failures++;                                                                \
+    }                                                                            \
+  } while (0)
+
+static int failures = 0;
+
+#define TARGET "HELLO"
+#define POP_N 20
+
+static void crossover_fn(ga_individual_t *child, ga_individual_t p1, ga_individual_t p2) {
+  if (!child || !p1 || !p2)
+    return;
+  uint32_t l1 = strlen(p1);
+  uint32_t l2 = strlen(p2);
+  if (l1 == 0 || l2 == 0)
+    return;
+  uint32_t c1 = rand() % l1;
+  uint32_t c2 = rand() % l2;
+  uint32_t len = c1 + (l2 - c2);
+  char *s = malloc(len + 1);
+  if (!s) {
+    free(*child);
+    *child = NULL;
+    return;
+  }
+  memcpy(s, p1, c1);
+  memcpy(s + c1, p2 + c2, l2 - c2);
+  s[len] = '\0';
+  free(*child);
+  *child = s;
+}
+
+static void mutation_fn(ga_individual_t *ind) {
+  if (!ind || !*ind)
+    return;
+  uint32_t l = strlen(*ind);
+  if (l == 0)
+    return;
+  (*ind)[rand() % l] = (char)(rand() % 26 + 'A');
+}
+
+static double fitness_fn(ga_individual_t ind, void const *data) {
+  if (!ind)
+    return DBL_MAX;
+  char const *target = (char const *)data;
+  double error = 0;
+  while (*ind && *target) {
+    error += abs((int)(*target++ - *ind++));
+  }
+  while (*ind) error += abs((int)*ind++);
+  while (*target) error += abs((int)*target++);
+  return error;
+}
+
+static void free_population(char *population[], int n) {
+  for (int i = 0; i < n; i++)
+    free(population[i]);
+}
+
+void test_generation() {
+  srand(42);
+  char *population[POP_N];
+
+  for (int i = 0; i < POP_N; i++) {
+    uint32_t len = 4 + rand() % 3;
+    char *s = malloc(len + 1);
+    if (!s) { free_population(population, i); exit(1); }
+    for (uint32_t j = 0; j < len; j++) {
+      s[j] = (char)(rand() % 26 + 'A');
+    }
+    s[len] = '\0';
+    population[i] = s;
+  }
+
+  double error = ga_generation(population, POP_N, 0.5, 1.0, fitness_fn, TARGET,
+                                crossover_fn, mutation_fn);
+
+  ASSERT(error >= 0, "error non-negative");
+
+  for (int i = POP_N - 1; i >= 0; i--) {
+    free(population[i]);
+  }
+}
+
+void test_convergence() {
+  srand(42);
+  char *population[POP_N];
+
+  for (int i = 0; i < POP_N; i++) {
+    uint32_t len = strlen(TARGET);
+    char *s = malloc(len + 1);
+    if (!s) { free_population(population, i); exit(1); }
+    for (uint32_t j = 0; j < len; j++) {
+      s[j] = (char)(rand() % 26 + 'A');
+    }
+    s[len] = '\0';
+    population[i] = s;
+  }
+
+  double error = 1;
+  int generations = 0;
+  while (error > 0 && generations < 500) {
+    error = ga_generation(population, POP_N, 0.5, 1.0, fitness_fn, TARGET,
+                          crossover_fn, mutation_fn);
+    generations++;
+  }
+
+  ASSERT(generations < 500, "converges within 500 generations");
+
+  for (int i = 0; i < POP_N; i++) {
+    free(population[i]);
+  }
+}
+
+void test_selection_rate() {
+  srand(42);
+  char *population[POP_N];
+
+  for (int i = 0; i < POP_N; i++) {
+    char *s = malloc(6);
+    if (!s) { free_population(population, i); exit(1); }
+    strcpy(s, "HELLO");
+    population[i] = s;
+  }
+
+  double error = ga_generation(population, POP_N, 0.5, 0.1, fitness_fn, TARGET,
+                                crossover_fn, mutation_fn);
+  ASSERT(error >= 0, "low mutation rate returns non-negative error");
+  ASSERT(error == 0, "all-population-matching-target has zero error");
+
+  for (int i = 0; i < POP_N; i++) {
+    free(population[i]);
+  }
+}
+
+int main() {
+  test_generation();
+  test_convergence();
+  test_selection_rate();
+
+  printf("test_genetic: %d failures\n", failures);
+  return failures;
+}