/* * Copyright (c) 2021, Spencer Dixon * * SPDX-License-Identifier: BSD-2-Clause */ #include #include #include 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(StringView 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(StringView needle, StringView 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(StringView needle, StringView haystack) { int recursion_count = 0; u8 matches[MAX_MATCHES] {}; return fuzzy_match_recursive(needle, haystack, 0, 0, nullptr, matches, 0, recursion_count); } }