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blame.c
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blame.c
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#include "git-compat-util.h"
#include "refs.h"
#include "object-store-ll.h"
#include "cache-tree.h"
#include "mergesort.h"
#include "convert.h"
#include "diff.h"
#include "diffcore.h"
#include "gettext.h"
#include "hex.h"
#include "path.h"
#include "read-cache.h"
#include "setup.h"
#include "tag.h"
#include "trace2.h"
#include "blame.h"
#include "alloc.h"
#include "commit-slab.h"
#include "bloom.h"
#include "commit-graph.h"
define_commit_slab(blame_suspects, struct blame_origin *);
static struct blame_suspects blame_suspects;
struct blame_origin *get_blame_suspects(struct commit *commit)
{
struct blame_origin **result;
result = blame_suspects_peek(&blame_suspects, commit);
return result ? *result : NULL;
}
static void set_blame_suspects(struct commit *commit, struct blame_origin *origin)
{
*blame_suspects_at(&blame_suspects, commit) = origin;
}
void blame_origin_decref(struct blame_origin *o)
{
if (o && --o->refcnt <= 0) {
struct blame_origin *p, *l = NULL;
if (o->previous)
blame_origin_decref(o->previous);
free(o->file.ptr);
/* Should be present exactly once in commit chain */
for (p = get_blame_suspects(o->commit); p; l = p, p = p->next) {
if (p == o) {
if (l)
l->next = p->next;
else
set_blame_suspects(o->commit, p->next);
free(o);
return;
}
}
die("internal error in blame_origin_decref");
}
}
/*
* Given a commit and a path in it, create a new origin structure.
* The callers that add blame to the scoreboard should use
* get_origin() to obtain shared, refcounted copy instead of calling
* this function directly.
*/
static struct blame_origin *make_origin(struct commit *commit, const char *path)
{
struct blame_origin *o;
FLEX_ALLOC_STR(o, path, path);
o->commit = commit;
o->refcnt = 1;
o->next = get_blame_suspects(commit);
set_blame_suspects(commit, o);
return o;
}
/*
* Locate an existing origin or create a new one.
* This moves the origin to front position in the commit util list.
*/
static struct blame_origin *get_origin(struct commit *commit, const char *path)
{
struct blame_origin *o, *l;
for (o = get_blame_suspects(commit), l = NULL; o; l = o, o = o->next) {
if (!strcmp(o->path, path)) {
/* bump to front */
if (l) {
l->next = o->next;
o->next = get_blame_suspects(commit);
set_blame_suspects(commit, o);
}
return blame_origin_incref(o);
}
}
return make_origin(commit, path);
}
static void verify_working_tree_path(struct repository *r,
struct commit *work_tree, const char *path)
{
struct commit_list *parents;
int pos;
for (parents = work_tree->parents; parents; parents = parents->next) {
const struct object_id *commit_oid = &parents->item->object.oid;
struct object_id blob_oid;
unsigned short mode;
if (!get_tree_entry(r, commit_oid, path, &blob_oid, &mode) &&
oid_object_info(r, &blob_oid, NULL) == OBJ_BLOB)
return;
}
pos = index_name_pos(r->index, path, strlen(path));
if (pos >= 0)
; /* path is in the index */
else if (-1 - pos < r->index->cache_nr &&
!strcmp(r->index->cache[-1 - pos]->name, path))
; /* path is in the index, unmerged */
else
die("no such path '%s' in HEAD", path);
}
static struct commit_list **append_parent(struct repository *r,
struct commit_list **tail,
const struct object_id *oid)
{
struct commit *parent;
parent = lookup_commit_reference(r, oid);
if (!parent)
die("no such commit %s", oid_to_hex(oid));
return &commit_list_insert(parent, tail)->next;
}
static void append_merge_parents(struct repository *r,
struct commit_list **tail)
{
int merge_head;
struct strbuf line = STRBUF_INIT;
merge_head = open(git_path_merge_head(r), O_RDONLY);
if (merge_head < 0) {
if (errno == ENOENT)
return;
die("cannot open '%s' for reading",
git_path_merge_head(r));
}
while (!strbuf_getwholeline_fd(&line, merge_head, '\n')) {
struct object_id oid;
if (get_oid_hex(line.buf, &oid))
die("unknown line in '%s': %s",
git_path_merge_head(r), line.buf);
tail = append_parent(r, tail, &oid);
}
close(merge_head);
strbuf_release(&line);
}
/*
* This isn't as simple as passing sb->buf and sb->len, because we
* want to transfer ownership of the buffer to the commit (so we
* must use detach).
*/
static void set_commit_buffer_from_strbuf(struct repository *r,
struct commit *c,
struct strbuf *sb)
{
size_t len;
void *buf = strbuf_detach(sb, &len);
set_commit_buffer(r, c, buf, len);
}
/*
* Prepare a dummy commit that represents the work tree (or staged) item.
* Note that annotating work tree item never works in the reverse.
*/
static struct commit *fake_working_tree_commit(struct repository *r,
struct diff_options *opt,
const char *path,
const char *contents_from,
struct object_id *oid)
{
struct commit *commit;
struct blame_origin *origin;
struct commit_list **parent_tail, *parent;
struct strbuf buf = STRBUF_INIT;
const char *ident;
time_t now;
int len;
struct cache_entry *ce;
unsigned mode;
struct strbuf msg = STRBUF_INIT;
repo_read_index(r);
time(&now);
commit = alloc_commit_node(r);
commit->object.parsed = 1;
commit->date = now;
parent_tail = &commit->parents;
parent_tail = append_parent(r, parent_tail, oid);
append_merge_parents(r, parent_tail);
verify_working_tree_path(r, commit, path);
origin = make_origin(commit, path);
if (contents_from)
ident = fmt_ident("External file (--contents)", "external.file",
WANT_BLANK_IDENT, NULL, 0);
else
ident = fmt_ident("Not Committed Yet", "not.committed.yet",
WANT_BLANK_IDENT, NULL, 0);
strbuf_addstr(&msg, "tree 0000000000000000000000000000000000000000\n");
for (parent = commit->parents; parent; parent = parent->next)
strbuf_addf(&msg, "parent %s\n",
oid_to_hex(&parent->item->object.oid));
strbuf_addf(&msg,
"author %s\n"
"committer %s\n\n"
"Version of %s from %s\n",
ident, ident, path,
(!contents_from ? path :
(!strcmp(contents_from, "-") ? "standard input" : contents_from)));
set_commit_buffer_from_strbuf(r, commit, &msg);
if (!contents_from || strcmp("-", contents_from)) {
struct stat st;
const char *read_from;
char *buf_ptr;
unsigned long buf_len;
if (contents_from) {
if (stat(contents_from, &st) < 0)
die_errno("Cannot stat '%s'", contents_from);
read_from = contents_from;
}
else {
if (lstat(path, &st) < 0)
die_errno("Cannot lstat '%s'", path);
read_from = path;
}
mode = canon_mode(st.st_mode);
switch (st.st_mode & S_IFMT) {
case S_IFREG:
if (opt->flags.allow_textconv &&
textconv_object(r, read_from, mode, null_oid(), 0, &buf_ptr, &buf_len))
strbuf_attach(&buf, buf_ptr, buf_len, buf_len + 1);
else if (strbuf_read_file(&buf, read_from, st.st_size) != st.st_size)
die_errno("cannot open or read '%s'", read_from);
break;
case S_IFLNK:
if (strbuf_readlink(&buf, read_from, st.st_size) < 0)
die_errno("cannot readlink '%s'", read_from);
break;
default:
die("unsupported file type %s", read_from);
}
}
else {
/* Reading from stdin */
mode = 0;
if (strbuf_read(&buf, 0, 0) < 0)
die_errno("failed to read from stdin");
}
convert_to_git(r->index, path, buf.buf, buf.len, &buf, 0);
origin->file.ptr = buf.buf;
origin->file.size = buf.len;
pretend_object_file(buf.buf, buf.len, OBJ_BLOB, &origin->blob_oid);
/*
* Read the current index, replace the path entry with
* origin->blob_sha1 without mucking with its mode or type
* bits; we are not going to write this index out -- we just
* want to run "diff-index --cached".
*/
discard_index(r->index);
repo_read_index(r);
len = strlen(path);
if (!mode) {
int pos = index_name_pos(r->index, path, len);
if (0 <= pos)
mode = r->index->cache[pos]->ce_mode;
else
/* Let's not bother reading from HEAD tree */
mode = S_IFREG | 0644;
}
ce = make_empty_cache_entry(r->index, len);
oidcpy(&ce->oid, &origin->blob_oid);
memcpy(ce->name, path, len);
ce->ce_flags = create_ce_flags(0);
ce->ce_namelen = len;
ce->ce_mode = create_ce_mode(mode);
add_index_entry(r->index, ce,
ADD_CACHE_OK_TO_ADD | ADD_CACHE_OK_TO_REPLACE);
cache_tree_invalidate_path(r->index, path);
return commit;
}
static int diff_hunks(mmfile_t *file_a, mmfile_t *file_b,
xdl_emit_hunk_consume_func_t hunk_func, void *cb_data, int xdl_opts)
{
xpparam_t xpp = {0};
xdemitconf_t xecfg = {0};
xdemitcb_t ecb = {NULL};
xpp.flags = xdl_opts;
xecfg.hunk_func = hunk_func;
ecb.priv = cb_data;
return xdi_diff(file_a, file_b, &xpp, &xecfg, &ecb);
}
static const char *get_next_line(const char *start, const char *end)
{
const char *nl = memchr(start, '\n', end - start);
return nl ? nl + 1 : end;
}
static int find_line_starts(int **line_starts, const char *buf,
unsigned long len)
{
const char *end = buf + len;
const char *p;
int *lineno;
int num = 0;
for (p = buf; p < end; p = get_next_line(p, end))
num++;
ALLOC_ARRAY(*line_starts, num + 1);
lineno = *line_starts;
for (p = buf; p < end; p = get_next_line(p, end))
*lineno++ = p - buf;
*lineno = len;
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->entry, hash);
found_entry = hashmap_get_entry(&result->map, entry,
/* member name */ entry, NULL);
if (found_entry) {
found_entry->count += 1;
} else {
entry->count = 1;
hashmap_add(&result->map, &entry->entry);
++entry;
}
}
}
static void free_fingerprint(struct fingerprint *f)
{
hashmap_clear(&f->map);
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_for_each_entry(&b->map, &iter, entry_b,
entry /* member name */) {
entry_a = hashmap_get_entry(&a->map, entry_b, entry, NULL);
if (entry_a) {
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);
hashmap_for_each_entry(&b->map, &iter, entry_b,
entry /* member name */) {
entry_a = hashmap_get_entry(&a->map, entry_b, entry, NULL);
if (entry_a) {
if (entry_a->count <= entry_b->count)
hashmap_remove(&a->map, &entry_b->entry, 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;
CALLOC_ARRAY(result, length_b);
CALLOC_ARRAY(second_best_result, length_b);
CALLOC_ARRAY(certainties, length_b);
/* See get_similarity() for details of similarities. */
similarity_count = length_b * (max_search_distance_a * 2 + 1);
CALLOC_ARRAY(similarities, 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)
{
int *line_starts;