package main

import (
	"testing"

	"github.com/lithammer/fuzzysearch/fuzzy"
)

// TestFuzzySmoke verifies the fuzzysearch dependency is importable and that
// its ranking API behaves as the scanner engine will expect.
//
// Note: this library does NOT expose a `fuzzy.Ratio` (0-100) function as the
// plan's Technical Details assumed. The relevant signal here is RankMatch,
// which returns 0 for an exact match, a small positive distance for near
// matches, and -1 when source is not a subsequence of target. Task 3 will
// convert this into a normalized 0.0-1.0 similarity score.
func TestFuzzySmoke(t *testing.T) {
	// Exact match scores 0 (distance).
	if got := fuzzy.RankMatch("the wall", "the wall"); got != 0 {
		t.Errorf("expected RankMatch of identical strings to be 0, got %d", got)
	}

	// Similar strings score closer to 0 than dissimilar ones, and a real
	// subsequence match returns a non-negative distance.
	similar := fuzzy.RankMatch("the wall", "the wall remastered")
	dissimilar := fuzzy.RankMatch("the wall", "completely different album")

	if similar < 0 {
		t.Errorf("expected similar to be a valid match (>=0), got %d", similar)
	}
	if dissimilar >= 0 {
		t.Errorf("expected dissimilar to be a non-match (-1), got %d", dissimilar)
	}
	if dissimilar != -1 {
		t.Errorf("expected dissimilar to be -1 (no subsequence match), got %d", dissimilar)
	}

	// A near match (valid, >=0) is preferable to a total miss (-1).
	if similar < 0 {
		t.Errorf("expected similar to be a valid match (>=0), got %d", similar)
	}
	if dissimilar != -1 {
		t.Errorf("expected dissimilar to be a non-match (-1), got %d", dissimilar)
	}
}