package main

import (
	"testing"

	"github.com/lithammer/fuzzysearch/fuzzy"

	"naviwatcher/internal/scanner"
)

// TestFuzzySmoke verifies the fuzzysearch dependency and the Levenshtein-based
// similarity primitive that the scanner engine actually uses (scanner.Similarity
// delegates to fuzzy.LevenshteinDistance). This guards against the library
// changing the distance semantics the engine relies on.
func TestFuzzySmoke(t *testing.T) {
	// Identical strings: zero edit distance.
	if d := fuzzy.LevenshteinDistance("the wall", "the wall"); d != 0 {
		t.Errorf("expected LevenshteinDistance of identical strings to be 0, got %d", d)
	}

	// A small edit (remaster suffix) is closer than a wholly different title.
	near := fuzzy.LevenshteinDistance("the wall", "the wall remastered")
	far := fuzzy.LevenshteinDistance("the wall", "completely different album")
	if near >= far {
		t.Errorf("expected near match distance (%d) < far match distance (%d)", near, far)
	}

	// The scanner's similarity score should report the near match as more
	// similar than the far one, and the identical pair as a perfect match.
	if s := scanner.Similarity("the wall", "the wall"); s != 1.0 {
		t.Errorf("expected Similarity of identical strings to be 1.0, got %f", s)
	}
	if scanner.Similarity("the wall", "the wall remastered") <= scanner.Similarity("the wall", "completely different album") {
		t.Error("expected near match to score higher than far match")
	}
}