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authorfaxe1008 <fabianblatz@gmail.com>2022-04-16 22:01:20 +0200
committerLinus Groh <mail@linusgroh.de>2022-04-20 18:34:09 +0200
commitb8bd66778213e27d350b28d830bc8c421944fc60 (patch)
tree5f4c0a171e06bca671d0a3165748de2e6722a84d /AK
parent1074c399f37be9c2e56215f7defaa1aa2eed125b (diff)
downloadserenity-b8bd66778213e27d350b28d830bc8c421944fc60.zip
AK: Add FuzzyMatch header
This patch adds a header containing the fuzzy match algorithm previously used in Assistant. The algorithm was moved to AK since there are many places where a search may benefit from fuzzyness.
Diffstat (limited to 'AK')
-rw-r--r--AK/FuzzyMatch.h144
1 files changed, 144 insertions, 0 deletions
diff --git a/AK/FuzzyMatch.h b/AK/FuzzyMatch.h
new file mode 100644
index 0000000000..1165cea050
--- /dev/null
+++ b/AK/FuzzyMatch.h
@@ -0,0 +1,144 @@
+/*
+ * Copyright (c) 2021, Spencer Dixon <spencercdixon@gmail.com>
+ *
+ * SPDX-License-Identifier: BSD-2-Clause
+ */
+
+#pragma once
+
+#include <AK/CharacterTypes.h>
+#include <AK/String.h>
+
+namespace AK {
+
+struct FuzzyMatchResult {
+ bool matched { false };
+ int score { 0 };
+};
+
+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;
+}
+
+static 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.
+static 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);
+}
+
+}
+using AK::fuzzy_match;
+using AK::FuzzyMatchResult;