diff options
Diffstat (limited to 'blame.c')
| -rw-r--r-- | blame.c | 642 |
1 files changed, 642 insertions, 0 deletions
@@ -339,6 +339,648 @@ static int find_line_starts(int **line_starts, const char *buf, return num; } +struct fingerprint_entry; + +/* A fingerprint is intended to loosely represent a string, such that two + * fingerprints can be quickly compared to give an indication of the similarity + * of the strings that they represent. + * + * A fingerprint is represented as a multiset of the lower-cased byte pairs in + * the string that it represents. Whitespace is added at each end of the + * string. Whitespace pairs are ignored. Whitespace is converted to '\0'. + * For example, the string "Darth Radar" will be converted to the following + * fingerprint: + * {"\0d", "da", "da", "ar", "ar", "rt", "th", "h\0", "\0r", "ra", "ad", "r\0"} + * + * The similarity between two fingerprints is the size of the intersection of + * their multisets, including repeated elements. See fingerprint_similarity for + * examples. + * + * For ease of implementation, the fingerprint is implemented as a map + * of byte pairs to the count of that byte pair in the string, instead of + * allowing repeated elements in a set. + */ +struct fingerprint { + struct hashmap map; + /* As we know the maximum number of entries in advance, it's + * convenient to store the entries in a single array instead of having + * the hashmap manage the memory. + */ + struct fingerprint_entry *entries; +}; + +/* A byte pair in a fingerprint. Stores the number of times the byte pair + * occurs in the string that the fingerprint represents. + */ +struct fingerprint_entry { + /* The hashmap entry - the hash represents the byte pair in its + * entirety so we don't need to store the byte pair separately. + */ + struct hashmap_entry entry; + /* The number of times the byte pair occurs in the string that the + * fingerprint represents. + */ + int count; +}; + +/* See `struct fingerprint` for an explanation of what a fingerprint is. + * \param result the fingerprint of the string is stored here. This must be + * freed later using free_fingerprint. + * \param line_begin the start of the string + * \param line_end the end of the string + */ +static void get_fingerprint(struct fingerprint *result, + const char *line_begin, + const char *line_end) +{ + unsigned int hash, c0 = 0, c1; + const char *p; + int max_map_entry_count = 1 + line_end - line_begin; + struct fingerprint_entry *entry = xcalloc(max_map_entry_count, + sizeof(struct fingerprint_entry)); + struct fingerprint_entry *found_entry; + + hashmap_init(&result->map, NULL, NULL, max_map_entry_count); + result->entries = entry; + for (p = line_begin; p <= line_end; ++p, c0 = c1) { + /* Always terminate the string with whitespace. + * Normalise whitespace to 0, and normalise letters to + * lower case. This won't work for multibyte characters but at + * worst will match some unrelated characters. + */ + if ((p == line_end) || isspace(*p)) + c1 = 0; + else + c1 = tolower(*p); + hash = c0 | (c1 << 8); + /* Ignore whitespace pairs */ + if (hash == 0) + continue; + hashmap_entry_init(entry, hash); + + found_entry = hashmap_get(&result->map, entry, NULL); + if (found_entry) { + found_entry->count += 1; + } else { + entry->count = 1; + hashmap_add(&result->map, entry); + ++entry; + } + } +} + +static void free_fingerprint(struct fingerprint *f) +{ + hashmap_free(&f->map, 0); + free(f->entries); +} + +/* Calculates the similarity between two fingerprints as the size of the + * intersection of their multisets, including repeated elements. See + * `struct fingerprint` for an explanation of the fingerprint representation. + * The similarity between "cat mat" and "father rather" is 2 because "at" is + * present twice in both strings while the similarity between "tim" and "mit" + * is 0. + */ +static int fingerprint_similarity(struct fingerprint *a, struct fingerprint *b) +{ + int intersection = 0; + struct hashmap_iter iter; + const struct fingerprint_entry *entry_a, *entry_b; + + hashmap_iter_init(&b->map, &iter); + + while ((entry_b = hashmap_iter_next(&iter))) { + if ((entry_a = hashmap_get(&a->map, entry_b, NULL))) { + intersection += entry_a->count < entry_b->count ? + entry_a->count : entry_b->count; + } + } + return intersection; +} + +/* Subtracts byte-pair elements in B from A, modifying A in place. + */ +static void fingerprint_subtract(struct fingerprint *a, struct fingerprint *b) +{ + struct hashmap_iter iter; + struct fingerprint_entry *entry_a; + const struct fingerprint_entry *entry_b; + + hashmap_iter_init(&b->map, &iter); + + while ((entry_b = hashmap_iter_next(&iter))) { + if ((entry_a = hashmap_get(&a->map, entry_b, NULL))) { + if (entry_a->count <= entry_b->count) + hashmap_remove(&a->map, entry_b, NULL); + else + entry_a->count -= entry_b->count; + } + } +} + +/* Calculate fingerprints for a series of lines. + * Puts the fingerprints in the fingerprints array, which must have been + * preallocated to allow storing line_count elements. + */ +static void get_line_fingerprints(struct fingerprint *fingerprints, + const char *content, const int *line_starts, + long first_line, long line_count) +{ + int i; + const char *linestart, *lineend; + + line_starts += first_line; + for (i = 0; i < line_count; ++i) { + linestart = content + line_starts[i]; + lineend = content + line_starts[i + 1]; + get_fingerprint(fingerprints + i, linestart, lineend); + } +} + +static void free_line_fingerprints(struct fingerprint *fingerprints, + int nr_fingerprints) +{ + int i; + + for (i = 0; i < nr_fingerprints; i++) + free_fingerprint(&fingerprints[i]); +} + +/* This contains the data necessary to linearly map a line number in one half + * of a diff chunk to the line in the other half of the diff chunk that is + * closest in terms of its position as a fraction of the length of the chunk. + */ +struct line_number_mapping { + int destination_start, destination_length, + source_start, source_length; +}; + +/* Given a line number in one range, offset and scale it to map it onto the + * other range. + * Essentially this mapping is a simple linear equation but the calculation is + * more complicated to allow performing it with integer operations. + * Another complication is that if a line could map onto many lines in the + * destination range then we want to choose the line at the center of those + * possibilities. + * Example: if the chunk is 2 lines long in A and 10 lines long in B then the + * first 5 lines in B will map onto the first line in the A chunk, while the + * last 5 lines will all map onto the second line in the A chunk. + * Example: if the chunk is 10 lines long in A and 2 lines long in B then line + * 0 in B will map onto line 2 in A, and line 1 in B will map onto line 7 in A. + */ +static int map_line_number(int line_number, + const struct line_number_mapping *mapping) +{ + return ((line_number - mapping->source_start) * 2 + 1) * + mapping->destination_length / + (mapping->source_length * 2) + + mapping->destination_start; +} + +/* Get a pointer to the element storing the similarity between a line in A + * and a line in B. + * + * The similarities are stored in a 2-dimensional array. Each "row" in the + * array contains the similarities for a line in B. The similarities stored in + * a row are the similarities between the line in B and the nearby lines in A. + * To keep the length of each row the same, it is padded out with values of -1 + * where the search range extends beyond the lines in A. + * For example, if max_search_distance_a is 2 and the two sides of a diff chunk + * look like this: + * a | m + * b | n + * c | o + * d | p + * e | q + * Then the similarity array will contain: + * [-1, -1, am, bm, cm, + * -1, an, bn, cn, dn, + * ao, bo, co, do, eo, + * bp, cp, dp, ep, -1, + * cq, dq, eq, -1, -1] + * Where similarities are denoted either by -1 for invalid, or the + * concatenation of the two lines in the diff being compared. + * + * \param similarities array of similarities between lines in A and B + * \param line_a the index of the line in A, in the same frame of reference as + * closest_line_a. + * \param local_line_b the index of the line in B, relative to the first line + * in B that similarities represents. + * \param closest_line_a the index of the line in A that is deemed to be + * closest to local_line_b. This must be in the same + * frame of reference as line_a. This value defines + * where similarities is centered for the line in B. + * \param max_search_distance_a maximum distance in lines from the closest line + * in A for other lines in A for which + * similarities may be calculated. + */ +static int *get_similarity(int *similarities, + int line_a, int local_line_b, + int closest_line_a, int max_search_distance_a) +{ + assert(abs(line_a - closest_line_a) <= + max_search_distance_a); + return similarities + line_a - closest_line_a + + max_search_distance_a + + local_line_b * (max_search_distance_a * 2 + 1); +} + +#define CERTAIN_NOTHING_MATCHES -2 +#define CERTAINTY_NOT_CALCULATED -1 + +/* Given a line in B, first calculate its similarities with nearby lines in A + * if not already calculated, then identify the most similar and second most + * similar lines. The "certainty" is calculated based on those two + * similarities. + * + * \param start_a the index of the first line of the chunk in A + * \param length_a the length in lines of the chunk in A + * \param local_line_b the index of the line in B, relative to the first line + * in the chunk. + * \param fingerprints_a array of fingerprints for the chunk in A + * \param fingerprints_b array of fingerprints for the chunk in B + * \param similarities 2-dimensional array of similarities between lines in A + * and B. See get_similarity() for more details. + * \param certainties array of values indicating how strongly a line in B is + * matched with some line in A. + * \param second_best_result array of absolute indices in A for the second + * closest match of a line in B. + * \param result array of absolute indices in A for the closest match of a line + * in B. + * \param max_search_distance_a maximum distance in lines from the closest line + * in A for other lines in A for which + * similarities may be calculated. + * \param map_line_number_in_b_to_a parameter to map_line_number(). + */ +static void find_best_line_matches( + int start_a, + int length_a, + int start_b, + int local_line_b, + struct fingerprint *fingerprints_a, + struct fingerprint *fingerprints_b, + int *similarities, + int *certainties, + int *second_best_result, + int *result, + const int max_search_distance_a, + const struct line_number_mapping *map_line_number_in_b_to_a) +{ + + int i, search_start, search_end, closest_local_line_a, *similarity, + best_similarity = 0, second_best_similarity = 0, + best_similarity_index = 0, second_best_similarity_index = 0; + + /* certainty has already been calculated so no need to redo the work */ + if (certainties[local_line_b] != CERTAINTY_NOT_CALCULATED) + return; + + closest_local_line_a = map_line_number( + local_line_b + start_b, map_line_number_in_b_to_a) - start_a; + + search_start = closest_local_line_a - max_search_distance_a; + if (search_start < 0) + search_start = 0; + + search_end = closest_local_line_a + max_search_distance_a + 1; + if (search_end > length_a) + search_end = length_a; + + for (i = search_start; i < search_end; ++i) { + similarity = get_similarity(similarities, + i, local_line_b, + closest_local_line_a, + max_search_distance_a); + if (*similarity == -1) { + /* This value will never exceed 10 but assert just in + * case + */ + assert(abs(i - closest_local_line_a) < 1000); + /* scale the similarity by (1000 - distance from + * closest line) to act as a tie break between lines + * that otherwise are equally similar. + */ + *similarity = fingerprint_similarity( + fingerprints_b + local_line_b, + fingerprints_a + i) * + (1000 - abs(i - closest_local_line_a)); + } + if (*similarity > best_similarity) { + second_best_similarity = best_similarity; + second_best_similarity_index = best_similarity_index; + best_similarity = *similarity; + best_similarity_index = i; + } else if (*similarity > second_best_similarity) { + second_best_similarity = *similarity; + second_best_similarity_index = i; + } + } + + if (best_similarity == 0) { + /* this line definitely doesn't match with anything. Mark it + * with this special value so it doesn't get invalidated and + * won't be recalculated. + */ + certainties[local_line_b] = CERTAIN_NOTHING_MATCHES; + result[local_line_b] = -1; + } else { + /* Calculate the certainty with which this line matches. + * If the line matches well with two lines then that reduces + * the certainty. However we still want to prioritise matching + * a line that matches very well with two lines over matching a + * line that matches poorly with one line, hence doubling + * best_similarity. + * This means that if we have + * line X that matches only one line with a score of 3, + * line Y that matches two lines equally with a score of 5, + * and line Z that matches only one line with a score or 2, + * then the lines in order of certainty are X, Y, Z. + */ + certainties[local_line_b] = best_similarity * 2 - + second_best_similarity; + + /* We keep both the best and second best results to allow us to + * check at a later stage of the matching process whether the + * result needs to be invalidated. + */ + result[local_line_b] = start_a + best_similarity_index; + second_best_result[local_line_b] = + start_a + second_best_similarity_index; + } +} + +/* + * This finds the line that we can match with the most confidence, and + * uses it as a partition. It then calls itself on the lines on either side of + * that partition. In this way we avoid lines appearing out of order, and + * retain a sensible line ordering. + * \param start_a index of the first line in A with which lines in B may be + * compared. + * \param start_b index of the first line in B for which matching should be + * done. + * \param length_a number of lines in A with which lines in B may be compared. + * \param length_b number of lines in B for which matching should be done. + * \param fingerprints_a mutable array of fingerprints in A. The first element + * corresponds to the line at start_a. + * \param fingerprints_b array of fingerprints in B. The first element + * corresponds to the line at start_b. + * \param similarities 2-dimensional array of similarities between lines in A + * and B. See get_similarity() for more details. + * \param certainties array of values indicating how strongly a line in B is + * matched with some line in A. + * \param second_best_result array of absolute indices in A for the second + * closest match of a line in B. + * \param result array of absolute indices in A for the closest match of a line + * in B. + * \param max_search_distance_a maximum distance in lines from the closest line + * in A for other lines in A for which + * similarities may be calculated. + * \param max_search_distance_b an upper bound on the greatest possible + * distance between lines in B such that they will + * both be compared with the same line in A + * according to max_search_distance_a. + * \param map_line_number_in_b_to_a parameter to map_line_number(). + */ +static void fuzzy_find_matching_lines_recurse( + int start_a, int start_b, + int length_a, int length_b, + struct fingerprint *fingerprints_a, + struct fingerprint *fingerprints_b, + int *similarities, + int *certainties, + int *second_best_result, + int *result, + int max_search_distance_a, + int max_search_distance_b, + const struct line_number_mapping *map_line_number_in_b_to_a) +{ + int i, invalidate_min, invalidate_max, offset_b, + second_half_start_a, second_half_start_b, + second_half_length_a, second_half_length_b, + most_certain_line_a, most_certain_local_line_b = -1, + most_certain_line_certainty = -1, + closest_local_line_a; + + for (i = 0; i < length_b; ++i) { + find_best_line_matches(start_a, + length_a, + start_b, + i, + fingerprints_a, + fingerprints_b, + similarities, + certainties, + second_best_result, + result, + max_search_distance_a, + map_line_number_in_b_to_a); + + if (certainties[i] > most_certain_line_certainty) { + most_certain_line_certainty = certainties[i]; + most_certain_local_line_b = i; + } + } + + /* No matches. */ + if (most_certain_local_line_b == -1) + return; + + most_certain_line_a = result[most_certain_local_line_b]; + + /* + * Subtract the most certain line's fingerprint in B from the matched + * fingerprint in A. This means that other lines in B can't also match + * the same parts of the line in A. + */ + fingerprint_subtract(fingerprints_a + most_certain_line_a - start_a, + fingerprints_b + most_certain_local_line_b); + + /* Invalidate results that may be affected by the choice of most + * certain line. + */ + invalidate_min = most_certain_local_line_b - max_search_distance_b; + invalidate_max = most_certain_local_line_b + max_search_distance_b + 1; + if (invalidate_min < 0) + invalidate_min = 0; + if (invalidate_max > length_b) + invalidate_max = length_b; + + /* As the fingerprint in A has changed, discard previously calculated + * similarity values with that fingerprint. + */ + for (i = invalidate_min; i < invalidate_max; ++i) { + closest_local_line_a = map_line_number( + i + start_b, map_line_number_in_b_to_a) - start_a; + + /* Check that the lines in A and B are close enough that there + * is a similarity value for them. + */ + if (abs(most_certain_line_a - start_a - closest_local_line_a) > + max_search_distance_a) { + continue; + } + + *get_similarity(similarities, most_certain_line_a - start_a, + i, closest_local_line_a, + max_search_distance_a) = -1; + } + + /* More invalidating of results that may be affected by the choice of + * most certain line. + * Discard the matches for lines in B that are currently matched with a + * line in A such that their ordering contradicts the ordering imposed + * by the choice of most certain line. + */ + for (i = most_certain_local_line_b - 1; i >= invalidate_min; --i) { + /* In this loop we discard results for lines in B that are + * before most-certain-line-B but are matched with a line in A + * that is after most-certain-line-A. + */ + if (certainties[i] >= 0 && + (result[i] >= most_certain_line_a || + second_best_result[i] >= most_certain_line_a)) { + certainties[i] = CERTAINTY_NOT_CALCULATED; + } + } + for (i = most_certain_local_line_b + 1; i < invalidate_max; ++i) { + /* In this loop we discard results for lines in B that are + * after most-certain-line-B but are matched with a line in A + * that is before most-certain-line-A. + */ + if (certainties[i] >= 0 && + (result[i] <= most_certain_line_a || + second_best_result[i] <= most_certain_line_a)) { + certainties[i] = CERTAINTY_NOT_CALCULATED; + } + } + + /* Repeat the matching process for lines before the most certain line. + */ + if (most_certain_local_line_b > 0) { + fuzzy_find_matching_lines_recurse( + start_a, start_b, + most_certain_line_a + 1 - start_a, + most_certain_local_line_b, + fingerprints_a, fingerprints_b, similarities, + certainties, second_best_result, result, + max_search_distance_a, + max_search_distance_b, + map_line_number_in_b_to_a); + } + /* Repeat the matching process for lines after the most certain line. + */ + if (most_certain_local_line_b + 1 < length_b) { + second_half_start_a = most_certain_line_a; + offset_b = most_certain_local_line_b + 1; + second_half_start_b = start_b + offset_b; + second_half_length_a = + length_a + start_a - second_half_start_a; + second_half_length_b = + length_b + start_b - second_half_start_b; + fuzzy_find_matching_lines_recurse( + second_half_start_a, second_half_start_b, + second_half_length_a, second_half_length_b, + fingerprints_a + second_half_start_a - start_a, + fingerprints_b + offset_b, + similarities + + offset_b * (max_search_distance_a * 2 + 1), + certainties + offset_b, + second_best_result + offset_b, result + offset_b, + max_search_distance_a, + max_search_distance_b, + map_line_number_in_b_to_a); + } +} + +/* Find the lines in the parent line range that most closely match the lines in + * the target line range. This is accomplished by matching fingerprints in each + * blame_origin, and choosing the best matches that preserve the line ordering. + * See struct fingerprint for details of fingerprint matching, and + * fuzzy_find_matching_lines_recurse for details of preserving line ordering. + * + * The performance is believed to be O(n log n) in the typical case and O(n^2) + * in a pathological case, where n is the number of lines in the target range. + */ +static int *fuzzy_find_matching_lines(struct blame_origin *parent, + struct blame_origin *target, + int tlno, int parent_slno, int same, + int parent_len) +{ + /* We use the terminology "A" for the left hand side of the diff AKA + * parent, and "B" for the right hand side of the diff AKA target. */ + int start_a = parent_slno; + int length_a = parent_len; + int start_b = tlno; + int length_b = same - tlno; + + struct line_number_mapping map_line_number_in_b_to_a = { + start_a, length_a, start_b, length_b + }; + + struct fingerprint *fingerprints_a = parent->fingerprints; + struct fingerprint *fingerprints_b = target->fingerprints; + + int i, *result, *second_best_result, + *certainties, *similarities, similarity_count; + + /* + * max_search_distance_a means that given a line in B, compare it to + * the line in A that is closest to its position, and the lines in A + * that are no greater than max_search_distance_a lines away from the + * closest line in A. + * + * max_search_distance_b is an upper bound on the greatest possible + * distance between lines in B such that they will both be compared + * with the same line in A according to max_search_distance_a. + */ + int max_search_distance_a = 10, max_search_distance_b; + + if (length_a <= 0) + return NULL; + + if (max_search_distance_a >= length_a) + max_search_distance_a = length_a ? length_a - 1 : 0; + + max_search_distance_b = ((2 * max_search_distance_a + 1) * length_b + - 1) / length_a; + + result = xcalloc(sizeof(int), length_b); + second_best_result = xcalloc(sizeof(int), length_b); + certainties = xcalloc(sizeof(int), length_b); + + /* See get_similarity() for details of similarities. */ + similarity_count = length_b * (max_search_distance_a * 2 + 1); + similarities = xcalloc(sizeof(int), similarity_count); + + for (i = 0; i < length_b; ++i) { + result[i] = -1; + second_best_result[i] = -1; + certainties[i] = CERTAINTY_NOT_CALCULATED; + } + + for (i = 0; i < similarity_count; ++i) + similarities[i] = -1; + + fuzzy_find_matching_lines_recurse(start_a, start_b, + length_a, length_b, + fingerprints_a + start_a, + fingerprints_b + start_b, + similarities, + certainties, + second_best_result, + result, + max_search_distance_a, + max_search_distance_b, + &map_line_number_in_b_to_a); + + free(similarities); + free(certainties); + free(second_best_result); + + return result; +} + static void fill_origin_fingerprints(struct blame_origin *o, mmfile_t *file) { int *line_starts; |