Normalize char before pattern lookup (#4252)

There is an edge-case in FuzzyMatchV1 during backward scan, related to
normalization: if string is initially denormalized (e.g. Unicode symbol),
backward scan will proceed further to the next char; however, when the
score is computed, the string is normalized first, then scanned based on
the pattern. This leads to accessing pattern index increment, which
itself leads to out-of-bound index access, resulting in a panic.

To illustrate the process, here's the sequence of operations when search
is perfored:

1. during backward scan by "minim" pattern

```
xxxxx Minímal example
      ^^^^^^^^^^^^
      ||||||||||||
      miniiiiiiiim <- compute score for this substring
```
2. during compute score by "minim" pattern
```
      Minímal exam
      minimal exam <- normalize chars before computing the score
      ^^^^^^
      ||||||
      minim <- at this point the pattern is already fully scanned and index
              is out-of-the-bound
```

In this commit the char is normalized during backward scan, to detect
properly the boundaries for the pattern.

src/algo/algo_test.go

@@ -200,3 +200,12 @@ func TestLongString(t *testing.T) {
 	bytes[math.MaxUint16] = 'z'
 	assertMatch(t, FuzzyMatchV2, true, true, string(bytes), "zx", math.MaxUint16, math.MaxUint16+2, scoreMatch*2+bonusConsecutive)
 }
+
+func TestLongStringWithNormalize(t *testing.T) {
+	bytes := make([]byte, 30000)
+	for i := range bytes {
+		bytes[i] = 'x'
+	}
+	unicodeString := string(bytes) + " Minímal example"
+	assertMatch2(t, FuzzyMatchV1, false, true, false, unicodeString, "minim", 30001, 30006, 140)
+}