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feat(diff): grouping optimization for linematch algorithm
This commit is contained in:
Jonathon
GitHub
parent
5f4895200a
commit
0381f5af5b
@ -2,6 +2,7 @@
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// it. PVS-Studio Static Code Analyzer for C, C++ and C#: http://www.viva64.com
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// it. PVS-Studio Static Code Analyzer for C, C++ and C#: http://www.viva64.com
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#include <assert.h>
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#include <assert.h>
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#include <math.h>
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#include <stdbool.h>
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#include <stdbool.h>
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#include <stddef.h>
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#include <stddef.h>
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#include <string.h>
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#include <string.h>
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@ -10,14 +11,19 @@
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#include "nvim/macros.h"
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#include "nvim/macros.h"
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#include "nvim/memory.h"
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#include "nvim/memory.h"
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// struct for running the diff linematch algorithm
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typedef struct {
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int *df_decision; // to keep track of this path traveled
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int df_lev_score; // to keep track of the total score of this path
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size_t df_path_idx; // current index of this path
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} diffcmppath_T;
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#define LN_MAX_BUFS 8
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#define LN_MAX_BUFS 8
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#define LN_DECISION_MAX 255 // pow(2, LN_MAX_BUFS(8)) - 1 = 255
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// struct for running the diff linematch algorithm
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typedef struct diffcmppath_S diffcmppath_T;
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struct diffcmppath_S {
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int df_lev_score; // to keep track of the total score of this path
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size_t df_path_n; // current index of this path
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int df_choice_mem[LN_DECISION_MAX + 1];
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int df_choice[LN_DECISION_MAX];
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diffcmppath_T *df_decision[LN_DECISION_MAX]; // to keep track of this path traveled
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size_t df_optimal_choice;
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};
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#ifdef INCLUDE_GENERATED_DECLARATIONS
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#ifdef INCLUDE_GENERATED_DECLARATIONS
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# include "linematch.c.generated.h"
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# include "linematch.c.generated.h"
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@ -64,26 +70,6 @@ static int matching_chars_iwhite(const char *s1, const char *s2)
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return matching;
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return matching;
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}
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}
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/// update the path of a point in the diff linematch algorithm
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/// @param diffcmppath
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/// @param score
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/// @param to
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/// @param from
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/// @param choice
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static void update_path_flat(diffcmppath_T *diffcmppath, int score, size_t to, size_t from,
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const int choice)
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{
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size_t path_idx = diffcmppath[from].df_path_idx;
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for (size_t k = 0; k < path_idx; k++) {
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diffcmppath[to].df_decision[k] = diffcmppath[from].df_decision[k];
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}
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diffcmppath[to].df_decision[path_idx] = choice;
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diffcmppath[to].df_lev_score = score;
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diffcmppath[to].df_path_idx = path_idx + 1;
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}
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#define MATCH_CHAR_MAX_LEN 800
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#define MATCH_CHAR_MAX_LEN 800
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/// Return matching characters between "s1" and "s2" whilst respecting sequence order.
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/// Return matching characters between "s1" and "s2" whilst respecting sequence order.
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@ -206,17 +192,14 @@ static void try_possible_paths(const int *df_iters, const size_t *paths, const i
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int matched_chars = count_n_matched_chars(current_lines, ndiffs, iwhite);
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int matched_chars = count_n_matched_chars(current_lines, ndiffs, iwhite);
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int score = diffcmppath[unwrapped_idx_from].df_lev_score + matched_chars;
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int score = diffcmppath[unwrapped_idx_from].df_lev_score + matched_chars;
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if (score > diffcmppath[unwrapped_idx_to].df_lev_score) {
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if (score > diffcmppath[unwrapped_idx_to].df_lev_score) {
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update_path_flat(diffcmppath, score, unwrapped_idx_to, unwrapped_idx_from, *choice);
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diffcmppath[unwrapped_idx_to].df_path_n = 1;
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}
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diffcmppath[unwrapped_idx_to].df_decision[0] = &diffcmppath[unwrapped_idx_from];
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} else {
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diffcmppath[unwrapped_idx_to].df_choice[0] = *choice;
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// initialize the 0, 0, 0 ... choice
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diffcmppath[unwrapped_idx_to].df_lev_score = score;
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size_t i = 0;
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} else if (score == diffcmppath[unwrapped_idx_to].df_lev_score) {
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while (i < ndiffs && df_iters[i] == 0) {
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size_t k = diffcmppath[unwrapped_idx_to].df_path_n++;
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i++;
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diffcmppath[unwrapped_idx_to].df_decision[k] = &diffcmppath[unwrapped_idx_from];
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if (i == ndiffs) {
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diffcmppath[unwrapped_idx_to].df_choice[k] = *choice;
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diffcmppath[0].df_lev_score = 0;
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diffcmppath[0].df_path_idx = 0;
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}
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}
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}
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}
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}
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return;
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return;
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@ -245,8 +228,7 @@ static size_t unwrap_indexes(const int *values, const int *diff_len, const size_
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for (size_t k = 0; k < ndiffs; k++) {
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for (size_t k = 0; k < ndiffs; k++) {
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num_unwrap_scalar /= (size_t)diff_len[k] + 1;
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num_unwrap_scalar /= (size_t)diff_len[k] + 1;
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// (k == 0) space optimization
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int n = values[k];
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int n = k == 0 ? values[k] % 2 : values[k];
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path_idx += num_unwrap_scalar * (size_t)n;
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path_idx += num_unwrap_scalar * (size_t)n;
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}
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}
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return path_idx;
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return path_idx;
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@ -354,7 +336,7 @@ size_t linematch_nbuffers(const char **diff_blk, const int *diff_len, const size
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size_t memsize_decisions = 0;
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size_t memsize_decisions = 0;
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for (size_t i = 0; i < ndiffs; i++) {
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for (size_t i = 0; i < ndiffs; i++) {
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assert(diff_len[i] >= 0);
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assert(diff_len[i] >= 0);
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memsize *= i == 0 ? 2 : (size_t)(diff_len[i] + 1);
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memsize *= (size_t)(diff_len[i] + 1);
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memsize_decisions += (size_t)diff_len[i];
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memsize_decisions += (size_t)diff_len[i];
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}
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}
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@ -362,7 +344,11 @@ size_t linematch_nbuffers(const char **diff_blk, const int *diff_len, const size
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diffcmppath_T *diffcmppath = xmalloc(sizeof(diffcmppath_T) * memsize);
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diffcmppath_T *diffcmppath = xmalloc(sizeof(diffcmppath_T) * memsize);
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// allocate memory here
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// allocate memory here
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for (size_t i = 0; i < memsize; i++) {
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for (size_t i = 0; i < memsize; i++) {
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diffcmppath[i].df_decision = xmalloc(memsize_decisions * sizeof(int));
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diffcmppath[i].df_lev_score = 0;
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diffcmppath[i].df_path_n = 0;
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for (size_t j = 0; j < (size_t)pow(2, (double)ndiffs); j++) {
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diffcmppath[i].df_choice_mem[j] = -1;
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}
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}
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}
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// memory for avoiding repetitive calculations of score
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// memory for avoiding repetitive calculations of score
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@ -370,18 +356,49 @@ size_t linematch_nbuffers(const char **diff_blk, const int *diff_len, const size
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populate_tensor(df_iters, 0, diffcmppath, diff_len, ndiffs, diff_blk, iwhite);
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populate_tensor(df_iters, 0, diffcmppath, diff_len, ndiffs, diff_blk, iwhite);
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const size_t u = unwrap_indexes(diff_len, diff_len, ndiffs);
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const size_t u = unwrap_indexes(diff_len, diff_len, ndiffs);
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const size_t best_path_idx = diffcmppath[u].df_path_idx;
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diffcmppath_T *startNode = &diffcmppath[u];
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const int *best_path_decisions = diffcmppath[u].df_decision;
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*decisions = xmalloc(sizeof(int) * best_path_idx);
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*decisions = xmalloc(sizeof(int) * memsize_decisions);
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for (size_t i = 0; i < best_path_idx; i++) {
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size_t n_optimal = 0;
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(*decisions)[i] = best_path_decisions[i];
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test_charmatch_paths(startNode, 0);
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while (startNode->df_path_n > 0) {
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size_t j = startNode->df_optimal_choice;
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(*decisions)[n_optimal++] = startNode->df_choice[j];
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startNode = startNode->df_decision[j];
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}
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// reverse array
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for (size_t i = 0; i < (n_optimal / 2); i++) {
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int tmp = (*decisions)[i];
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(*decisions)[i] = (*decisions)[n_optimal - 1 - i];
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(*decisions)[n_optimal - 1 - i] = tmp;
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}
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}
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for (size_t i = 0; i < memsize; i++) {
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xfree(diffcmppath[i].df_decision);
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}
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xfree(diffcmppath);
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xfree(diffcmppath);
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return best_path_idx;
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return n_optimal;
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}
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// returns the minimum amount of path changes from start to end
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static size_t test_charmatch_paths(diffcmppath_T *node, int lastdecision)
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{
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// memoization
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if (node->df_choice_mem[lastdecision] == -1) {
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if (node->df_path_n == 0) {
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// we have reached the end of the tree
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node->df_choice_mem[lastdecision] = 0;
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} else {
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size_t minimum_turns = SIZE_MAX; // the minimum amount of turns required to reach the end
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for (size_t i = 0; i < node->df_path_n; i++) {
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// recurse
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size_t t = test_charmatch_paths(node->df_decision[i], node->df_choice[i]) +
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(lastdecision != node->df_choice[i] ? 1 : 0);
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if (t < minimum_turns) {
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node->df_optimal_choice = i;
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minimum_turns = t;
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}
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}
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node->df_choice_mem[lastdecision] = (int)minimum_turns;
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}
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}
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return (size_t)node->df_choice_mem[lastdecision];
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}
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}
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@ -779,6 +779,192 @@ something
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end)
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end)
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end)
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end)
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describe('setup a diff with 2 files and set linematch:30', function()
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before_each(function()
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feed(':set diffopt+=linematch:30<cr>')
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local f1 = [[
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// abc d
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// d
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// d
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]]
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local f2 = [[
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abc d
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d
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]]
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write_file(fname, f1, false)
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write_file(fname_2, f2, false)
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reread()
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end)
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it('display results', function()
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screen:expect([[
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{1: }{10: 1 }{4:^ }│{1: }{10: }{2:--------------------------------------------}|
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{1: }{10: 2 }{9:abc d }│{1: }{10: 1 }{8:// }{9:abc d }|
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{1: }{10: 3 }{9:d }│{1: }{10: 2 }{8:// }{9:d }|
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{1: }{10: }{2:-------------------------------------------}│{1: }{10: 3 }{4:// d }|
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{1: }{10: 4 } │{1: }{10: 4 } |
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{7:Xtest-functional-diff-screen-1.2 }{3:Xtest-functional-diff-screen-1 }|
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:e |
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]])
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end)
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end)
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describe('setup a diff with 2 files and set linematch:30, with ignore white', function()
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before_each(function()
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feed(':set diffopt+=linematch:30<cr>:set diffopt+=iwhiteall<cr>')
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local f1 = [[
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void testFunction () {
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for (int i = 0; i < 10; i++) {
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for (int j = 0; j < 10; j++) {
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}
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}
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}
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]]
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local f2 = [[
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void testFunction () {
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// for (int j = 0; j < 10; i++) {
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// }
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}
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]]
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write_file(fname, f1, false)
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write_file(fname_2, f2, false)
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reread()
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end)
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it('display results', function()
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screen:expect([[
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{1: }{10: 1 }^void testFunction () { │{1: }{10: 1 }void testFunction () { |
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{1: }{10: }{2:-------------------------------------------}│{1: }{10: 2 }{4: for (int i = 0; i < 10; i++) { }|
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{1: }{10: 2 }{9: }{8:// for (int j = 0; j < 10; i}{9:++) { }│{1: }{10: 3 }{9: }{8:for (int j = 0; j < 10; j}{9:++) { }|
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{1: }{10: 3 }{9: }{8:// }{9:} }│{1: }{10: 4 }{9: } }|
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{1: }{10: }{2:-------------------------------------------}│{1: }{10: 5 }{4: } }|
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{1: }{10: 4 }} │{1: }{10: 6 }} |
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{1: }{10: 5 } │{1: }{10: 7 } |
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{7:Xtest-functional-diff-screen-1.2 }{3:Xtest-functional-diff-screen-1 }|
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:e |
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]])
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end)
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end)
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describe('a diff that would result in multiple groups before grouping optimization', function()
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before_each(function()
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feed(':set diffopt+=linematch:30<cr>')
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local f1 = [[
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!A
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!B
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!C
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]]
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local f2 = [[
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?Z
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?A
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?B
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?C
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?A
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?B
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?B
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?C
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]]
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write_file(fname, f1, false)
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write_file(fname_2, f2, false)
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reread()
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end)
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it('display results', function()
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screen:expect([[
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{1: }{10: 1 }{4:^?Z }│{1: }{10: }{2:--------------------------------------------}|
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{1: }{10: 2 }{8:?}{9:A }│{1: }{10: 1 }{8:!}{9:A }|
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{1: }{10: 3 }{8:?}{9:B }│{1: }{10: 2 }{8:!}{9:B }|
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{1: }{10: 4 }{8:?}{9:C }│{1: }{10: 3 }{8:!}{9:C }|
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{1: }{10: 5 }{4:?A }│{1: }{10: }{2:--------------------------------------------}|
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{1: }{10: 6 }{4:?B }│{1: }{10: }{2:--------------------------------------------}|
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{1: }{10: 7 }{4:?B }│{1: }{10: }{2:--------------------------------------------}|
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{1: }{10: 8 }{4:?C }│{1: }{10: }{2:--------------------------------------------}|
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{1: }{10: 9 } │{1: }{10: 4 } |
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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{6:~ }│{6:~ }|
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||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{7:Xtest-functional-diff-screen-1.2 }{3:Xtest-functional-diff-screen-1 }|
|
||||||
|
:e |
|
||||||
|
]])
|
||||||
|
end)
|
||||||
|
end)
|
||||||
|
describe('a diff that would result in multiple groups before grouping optimization', function()
|
||||||
|
before_each(function()
|
||||||
|
feed(':set diffopt+=linematch:30<cr>')
|
||||||
|
local f1 = [[
|
||||||
|
!A
|
||||||
|
!B
|
||||||
|
!C
|
||||||
|
]]
|
||||||
|
local f2 = [[
|
||||||
|
?A
|
||||||
|
?Z
|
||||||
|
?B
|
||||||
|
?C
|
||||||
|
?A
|
||||||
|
?B
|
||||||
|
?C
|
||||||
|
?C
|
||||||
|
]]
|
||||||
|
write_file(fname, f1, false)
|
||||||
|
write_file(fname_2, f2, false)
|
||||||
|
reread()
|
||||||
|
end)
|
||||||
|
|
||||||
|
it('display results', function()
|
||||||
|
screen:expect([[
|
||||||
|
{1: }{10: 1 }{4:^?A }│{1: }{10: }{2:--------------------------------------------}|
|
||||||
|
{1: }{10: 2 }{4:?Z }│{1: }{10: }{2:--------------------------------------------}|
|
||||||
|
{1: }{10: 3 }{4:?B }│{1: }{10: }{2:--------------------------------------------}|
|
||||||
|
{1: }{10: 4 }{4:?C }│{1: }{10: }{2:--------------------------------------------}|
|
||||||
|
{1: }{10: 5 }{8:?}{9:A }│{1: }{10: 1 }{8:!}{9:A }|
|
||||||
|
{1: }{10: 6 }{8:?}{9:B }│{1: }{10: 2 }{8:!}{9:B }|
|
||||||
|
{1: }{10: 7 }{8:?}{9:C }│{1: }{10: 3 }{8:!}{9:C }|
|
||||||
|
{1: }{10: 8 }{4:?C }│{1: }{10: }{2:--------------------------------------------}|
|
||||||
|
{1: }{10: 9 } │{1: }{10: 4 } |
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{6:~ }│{6:~ }|
|
||||||
|
{7:Xtest-functional-diff-screen-1.2 }{3:Xtest-functional-diff-screen-1 }|
|
||||||
|
:e |
|
||||||
|
]])
|
||||||
|
end)
|
||||||
|
end)
|
||||||
describe('setup a diff with 2 files and set linematch:10', function()
|
describe('setup a diff with 2 files and set linematch:10', function()
|
||||||
before_each(function()
|
before_each(function()
|
||||||
feed(':set diffopt+=linematch:10<cr>')
|
feed(':set diffopt+=linematch:10<cr>')
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user