1 files changed, 135 insertions, 0 deletions
diff --git a/AK/FuzzyMatch.cpp b/AK/FuzzyMatch.cpp
new file mode 100644
index 0000000000..3420e75e8e
--- /dev/null
+++ b/AK/FuzzyMatch.cpp
@@ -0,0 +1,135 @@
+/*
+ * Copyright (c) 2021, Spencer Dixon <spencercdixon@gmail.com>
+ *
+ * SPDX-License-Identifier: BSD-2-Clause
+ */
+
+#include <AK/CharacterTypes.h>
+#include <AK/FuzzyMatch.h>
+
+namespace AK {
+
+static constexpr int const RECURSION_LIMIT = 10;
+static constexpr int const MAX_MATCHES = 256;
+
+// Bonuses and penalties are used to build up a final score for the match.
+static constexpr int const SEQUENTIAL_BONUS = 15;            // bonus for adjacent matches (needle: 'ca', haystack: 'cat')
+static constexpr int const SEPARATOR_BONUS = 30;             // bonus if match occurs after a separator ('_' or ' ')
+static constexpr int const CAMEL_BONUS = 30;                 // bonus if match is uppercase and prev is lower (needle: 'myF' haystack: '/path/to/myFile.txt')
+static constexpr int const FIRST_LETTER_BONUS = 20;          // bonus if the first letter is matched (needle: 'c' haystack: 'cat')
+static constexpr int const LEADING_LETTER_PENALTY = -5;      // penalty applied for every letter in str before the first match
+static constexpr int const MAX_LEADING_LETTER_PENALTY = -15; // maximum penalty for leading letters
+static constexpr int const UNMATCHED_LETTER_PENALTY = -1;    // penalty for every letter that doesn't matter
+
+static int calculate_score(String const& string, u8* index_points, size_t index_points_size)
+{
+    int out_score = 100;
+
+    int penalty = LEADING_LETTER_PENALTY * index_points[0];
+    if (penalty < MAX_LEADING_LETTER_PENALTY)
+        penalty = MAX_LEADING_LETTER_PENALTY;
+    out_score += penalty;
+
+    int unmatched = string.length() - index_points_size;
+    out_score += UNMATCHED_LETTER_PENALTY * unmatched;
+
+    for (size_t i = 0; i < index_points_size; i++) {
+        u8 current_idx = index_points[i];
+
+        if (current_idx == 0)
+            out_score += FIRST_LETTER_BONUS;
+
+        if (i == 0)
+            continue;
+
+        u8 previous_idx = index_points[i - 1];
+        if (current_idx - 1 == previous_idx)
+            out_score += SEQUENTIAL_BONUS;
+
+        u32 current_character = string[current_idx];
+        u32 neighbor_character = string[current_idx - 1];
+
+        if (neighbor_character != to_ascii_uppercase(neighbor_character) && current_character != to_ascii_lowercase(current_character))
+            out_score += CAMEL_BONUS;
+
+        if (neighbor_character == '_' || neighbor_character == ' ')
+            out_score += SEPARATOR_BONUS;
+    }
+
+    return out_score;
+}
+
+FuzzyMatchResult fuzzy_match_recursive(String const& needle, String const& haystack, size_t needle_idx, size_t haystack_idx,
+    u8 const* src_matches, u8* matches, int next_match, int& recursion_count)
+{
+    int out_score = 0;
+
+    ++recursion_count;
+    if (recursion_count >= RECURSION_LIMIT)
+        return { false, out_score };
+
+    if (needle.length() == needle_idx || haystack.length() == haystack_idx)
+        return { false, out_score };
+
+    bool had_recursive_match = false;
+    constexpr size_t recursive_match_limit = 256;
+    u8 best_recursive_matches[recursive_match_limit];
+    int best_recursive_score = 0;
+
+    bool first_match = true;
+    while (needle_idx < needle.length() && haystack_idx < haystack.length()) {
+
+        if (to_ascii_lowercase(needle[needle_idx]) == to_ascii_lowercase(haystack[haystack_idx])) {
+            if (next_match >= MAX_MATCHES)
+                return { false, out_score };
+
+            if (first_match && src_matches) {
+                memcpy(matches, src_matches, next_match);
+                first_match = false;
+            }
+
+            u8 recursive_matches[recursive_match_limit] {};
+            auto result = fuzzy_match_recursive(needle, haystack, needle_idx, haystack_idx + 1, matches, recursive_matches, next_match, recursion_count);
+            if (result.matched) {
+                if (!had_recursive_match || result.score > best_recursive_score) {
+                    memcpy(best_recursive_matches, recursive_matches, recursive_match_limit);
+                    best_recursive_score = result.score;
+                }
+                had_recursive_match = true;
+            }
+            matches[next_match++] = haystack_idx;
+            needle_idx++;
+        }
+        haystack_idx++;
+    }
+
+    bool matched = needle_idx == needle.length();
+    if (!matched)
+        return { false, out_score };
+
+    out_score = calculate_score(haystack, matches, next_match);
+
+    if (had_recursive_match && (best_recursive_score > out_score)) {
+        memcpy(matches, best_recursive_matches, MAX_MATCHES);
+        out_score = best_recursive_score;
+    }
+
+    return { true, out_score };
+}
+
+// This fuzzy_match algorithm is based off a similar algorithm used by Sublime Text. The key insight is that instead
+// of doing a total in the distance between characters (I.E. Levenshtein Distance), we apply some meaningful heuristics
+// related to our dataset that we're trying to match to build up a score. Scores can then be sorted and displayed
+// with the highest at the top.
+//
+// Scores are not normalized between any values and have no particular meaning. The starting value is 100 and when we
+// detect good indicators of a match we add to the score. When we detect bad indicators, we penalize the match and subtract
+// from its score. Therefore, the longer the needle/haystack the greater the range of scores could be.
+FuzzyMatchResult fuzzy_match(String const& needle, String const& haystack)
+{
+    int recursion_count = 0;
+    u8 matches[MAX_MATCHES] {};
+    return fuzzy_match_recursive(needle, haystack, 0, 0, nullptr, matches, 0, recursion_count);
+}
+
+}