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fix: Update C code for compatibility with the MSVC compiler (#949)

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* Replace VLA with malloc
Replace VLA with malloc to make C code
compatible with cl compiler on Windows.

* Fix C code for CI compiler.

* Fix C code compability to CI.

* check the trigger
This commit is contained in:
Yudong Jin
2023-11-17 00:29:54 +08:00
committed by GitHub
parent e4aa76ed3e
commit f7c41b6bef
23 changed files with 235 additions and 174 deletions
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14
codes/c/chapter_dynamic_programming/climbing_stairs_constraint_dp.c
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@@ -12,8 +12,10 @@ int climbingStairsConstraintDP(int n) {
return 1;
}
// 初始化 dp 表，用于存储子问题的解
int dp[n + 1][3];
memset(dp, 0, sizeof(dp));
int **dp = malloc((n + 1) * sizeof(int *));
for (int i = 0; i <= n; i++) {
dp[i] = calloc(3, sizeof(int));
}
// 初始状态：预设最小子问题的解
dp[1][1] = 1;
dp[1][2] = 0;
@@ -24,7 +26,13 @@ int climbingStairsConstraintDP(int n) {
dp[i][1] = dp[i - 1][2];
dp[i][2] = dp[i - 2][1] + dp[i - 2][2];
}
return dp[n][1] + dp[n][2];
int res = dp[n][1] + dp[n][2];
// 释放内存
for (int i = 0; i <= n; i++) {
free(dp[i]);
}
free(dp);
return res;
}
/* Driver Code */

28
codes/c/chapter_dynamic_programming/coin_change.c
View File

@@ -7,7 +7,7 @@
#include "../utils/common.h"
/* 求最小值 */
int min(int a, int b) {
int myMin(int a, int b) {
return a < b ? a : b;
}
@@ -16,8 +16,10 @@ int coinChangeDP(int coins[], int amt, int coinsSize) {
int n = coinsSize;
int MAX = amt + 1;
// 初始化 dp 表
int dp[n + 1][amt + 1];
memset(dp, 0, sizeof(dp));
int **dp = malloc((n + 1) * sizeof(int *));
for (int i = 0; i <= n; i++) {
dp[i] = calloc(amt + 1, sizeof(int));
}
// 状态转移：首行首列
for (int a = 1; a <= amt; a++) {
dp[0][a] = MAX;
@@ -30,11 +32,17 @@ int coinChangeDP(int coins[], int amt, int coinsSize) {
dp[i][a] = dp[i - 1][a];
} else {
// 不选和选硬币 i 这两种方案的较小值
dp[i][a] = min(dp[i - 1][a], dp[i][a - coins[i - 1]] + 1);
dp[i][a] = myMin(dp[i - 1][a], dp[i][a - coins[i - 1]] + 1);
}
}
}
return dp[n][amt] != MAX ? dp[n][amt] : -1;
int res = dp[n][amt] != MAX ? dp[n][amt] : -1;
// 释放内存
for (int i = 0; i <= n; i++) {
free(dp[i]);
}
free(dp);
return res;
}
/* 零钱兑换：空间优化后的动态规划 */
@@ -42,8 +50,7 @@ int coinChangeDPComp(int coins[], int amt, int coinsSize) {
int n = coinsSize;
int MAX = amt + 1;
// 初始化 dp 表
int dp[amt + 1];
memset(dp, MAX, sizeof(dp));
int *dp = calloc(amt + 1, sizeof(int));
dp[0] = 0;
// 状态转移
for (int i = 1; i <= n; i++) {
@@ -53,11 +60,14 @@ int coinChangeDPComp(int coins[], int amt, int coinsSize) {
dp[a] = dp[a];
} else {
// 不选和选硬币 i 这两种方案的较小值
dp[a] = min(dp[a], dp[a - coins[i - 1]] + 1);
dp[a] = myMin(dp[a], dp[a - coins[i - 1]] + 1);
}
}
}
return dp[amt] != MAX ? dp[amt] : -1;
int res = dp[amt] != MAX ? dp[amt] : -1;
// 释放内存
free(dp);
return res;
}
/* Driver code */

22
codes/c/chapter_dynamic_programming/coin_change_ii.c
View File

@@ -10,8 +10,10 @@
int coinChangeIIDP(int coins[], int amt, int coinsSize) {
int n = coinsSize;
// 初始化 dp 表
int dp[n + 1][amt + 1];
memset(dp, 0, sizeof(dp));
int **dp = malloc((n + 1) * sizeof(int *));
for (int i = 0; i <= n; i++) {
dp[i] = calloc(amt + 1, sizeof(int));
}
// 初始化首列
for (int i = 0; i <= n; i++) {
dp[i][0] = 1;
@@ -28,15 +30,20 @@ int coinChangeIIDP(int coins[], int amt, int coinsSize) {
}
}
}
return dp[n][amt];
int res = dp[n][amt];
// 释放内存
for (int i = 0; i <= n; i++) {
free(dp[i]);
}
free(dp);
return res;
}
/* 零钱兑换 II：空间优化后的动态规划 */
int coinChangeIIDPComp(int coins[], int amt, int coinsSize) {
int n = coinsSize;
// 初始化 dp 表
int dp[amt + 1];
memset(dp, 0, sizeof(dp));
int *dp = calloc(amt + 1, sizeof(int));
dp[0] = 1;
// 状态转移
for (int i = 1; i <= n; i++) {
@@ -50,7 +57,10 @@ int coinChangeIIDPComp(int coins[], int amt, int coinsSize) {
}
}
}
return dp[amt];
int res = dp[amt];
// 释放内存
free(dp);
return res;
}
/* Driver code */

47
codes/c/chapter_dynamic_programming/edit_distance.c
View File

@@ -7,12 +7,12 @@
#include "../utils/common.h"
/* 求最小值 */
int min(int a, int b) {
int myMin(int a, int b) {
return a < b ? a : b;
}
/* 编辑距离：暴力搜索 */
int editDistanceDFS(char *s, char *t, int i, int j) {
int editDistanceDFS(char *s, char *t, int i, int j) {
// 若 s 和 t 都为空，则返回 0
if (i == 0 && j == 0)
return 0;
@@ -30,11 +30,11 @@ int editDistanceDFS(char *s, char *t, int i, int j) {
int del = editDistanceDFS(s, t, i - 1, j);
int replace = editDistanceDFS(s, t, i - 1, j - 1);
// 返回最少编辑步数
return min(min(insert, del), replace) + 1;
return myMin(myMin(insert, del), replace) + 1;
}
/* 编辑距离：记忆化搜索 */
int editDistanceDFSMem(char *s, char *t, int memCols, int mem[][memCols], int i, int j) {
int editDistanceDFSMem(char *s, char *t, int memCols, int **mem, int i, int j) {
// 若 s 和 t 都为空，则返回 0
if (i == 0 && j == 0)
return 0;
@@ -55,14 +55,16 @@ int editDistanceDFSMem(char *s, char *t, int memCols, int mem[][memCols], int i,
int del = editDistanceDFSMem(s, t, memCols, mem, i - 1, j);
int replace = editDistanceDFSMem(s, t, memCols, mem, i - 1, j - 1);
// 记录并返回最少编辑步数
mem[i][j] = min(min(insert, del), replace) + 1;
mem[i][j] = myMin(myMin(insert, del), replace) + 1;
return mem[i][j];
}
/* 编辑距离：动态规划 */
int editDistanceDP(char *s, char *t, int n, int m) {
int dp[n + 1][m + 1];
memset(dp, 0, sizeof(dp));
int **dp = malloc((n + 1) * sizeof(int *));
for (int i = 0; i <= n; i++) {
dp[i] = calloc(m + 1, sizeof(int));
}
// 状态转移：首行首列
for (int i = 1; i <= n; i++) {
dp[i][0] = i;
@@ -78,17 +80,21 @@ int editDistanceDP(char *s, char *t, int n, int m) {
dp[i][j] = dp[i - 1][j - 1];
} else {
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
dp[i][j] = min(min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
dp[i][j] = myMin(myMin(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
}
}
}
return dp[n][m];
int res = dp[n][m];
// 释放内存
for (int i = 0; i <= n; i++) {
free(dp[i]);
}
return res;
}
/* 编辑距离：空间优化后的动态规划 */
int editDistanceDPComp(char *s, char *t, int n, int m) {
int dp[m + 1];
memset(dp, 0, sizeof(dp));
int *dp = calloc(m + 1, sizeof(int));
// 状态转移：首行
for (int j = 1; j <= m; j++) {
dp[j] = j;
@@ -106,12 +112,15 @@ int editDistanceDPComp(char *s, char *t, int n, int m) {
dp[j] = leftup;
} else {
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
dp[j] = min(min(dp[j - 1], dp[j]), leftup) + 1;
dp[j] = myMin(myMin(dp[j - 1], dp[j]), leftup) + 1;
}
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
}
}
return dp[m];
int res = dp[m];
// 释放内存
free(dp);
return res;
}
/* Driver Code */
@@ -125,10 +134,18 @@ int main() {
printf("将 %s 更改为 %s 最少需要编辑 %d 步\n", s, t, res);
// 记忆化搜索
int mem[n + 1][m + 1];
memset(mem, -1, sizeof(mem));
int **mem = malloc((n + 1) * sizeof(int *));
for (int i = 0; i <= n; i++) {
mem[i] = malloc((m + 1) * sizeof(int));
memset(mem[i], -1, (m + 1) * sizeof(int));
}
res = editDistanceDFSMem(s, t, m + 1, mem, n, m);
printf("将 %s 更改为 %s 最少需要编辑 %d 步\n", s, t, res);
// 释放内存
for (int i = 0; i <= n; i++) {
free(mem[i]);
}
free(mem);
// 动态规划
res = editDistanceDP(s, t, n, m);

45
codes/c/chapter_dynamic_programming/knapsack.c
View File

@@ -7,7 +7,7 @@
#include "../utils/common.h"
/* 求最大值 */
int max(int a, int b) {
int myMax(int a, int b) {
return a > b ? a : b;
}
@@ -25,11 +25,11 @@ int knapsackDFS(int wgt[], int val[], int i, int c) {
int no = knapsackDFS(wgt, val, i - 1, c);
int yes = knapsackDFS(wgt, val, i - 1, c - wgt[i - 1]) + val[i - 1];
// 返回两种方案中价值更大的那一个
return max(no, yes);
return myMax(no, yes);
}
/* 0-1 背包：记忆化搜索 */
int knapsackDFSMem(int wgt[], int val[], int memCols, int mem[][memCols], int i, int c) {
int knapsackDFSMem(int wgt[], int val[], int memCols, int **mem, int i, int c) {
// 若已选完所有物品或背包无容量，则返回价值 0
if (i == 0 || c == 0) {
return 0;
@@ -46,7 +46,7 @@ int knapsackDFSMem(int wgt[], int val[], int memCols, int mem[][memCols], int i,
int no = knapsackDFSMem(wgt, val, memCols, mem, i - 1, c);
int yes = knapsackDFSMem(wgt, val, memCols, mem, i - 1, c - wgt[i - 1]) + val[i - 1];
// 记录并返回两种方案中价值更大的那一个
mem[i][c] = max(no, yes);
mem[i][c] = myMax(no, yes);
return mem[i][c];
}
@@ -54,8 +54,10 @@ int knapsackDFSMem(int wgt[], int val[], int memCols, int mem[][memCols], int i,
int knapsackDP(int wgt[], int val[], int cap, int wgtSize) {
int n = wgtSize;
// 初始化 dp 表
int dp[n + 1][cap + 1];
memset(dp, 0, sizeof(dp));
int **dp = malloc((n + 1) * sizeof(int *));
for (int i = 0; i <= n; i++) {
dp[i] = calloc(cap + 1, sizeof(int));
}
// 状态转移
for (int i = 1; i <= n; i++) {
for (int c = 1; c <= cap; c++) {
@@ -64,30 +66,37 @@ int knapsackDP(int wgt[], int val[], int cap, int wgtSize) {
dp[i][c] = dp[i - 1][c];
} else {
// 不选和选物品 i 这两种方案的较大值
dp[i][c] = max(dp[i - 1][c], dp[i - 1][c - wgt[i - 1]] + val[i - 1]);
dp[i][c] = myMax(dp[i - 1][c], dp[i - 1][c - wgt[i - 1]] + val[i - 1]);
}
}
}
return dp[n][cap];
int res = dp[n][cap];
// 释放内存
for (int i = 0; i <= n; i++) {
free(dp[i]);
}
return res;
}
/* 0-1 背包：空间优化后的动态规划 */
int knapsackDPComp(int wgt[], int val[], int cap, int wgtSize) {
int n = wgtSize;
// 初始化 dp 表
int dp[cap + 1];
memset(dp, 0, sizeof(dp));
int *dp = calloc(cap + 1, sizeof(int));
// 状态转移
for (int i = 1; i <= n; i++) {
// 倒序遍历
for (int c = cap; c >= 1; c--) {
if (wgt[i - 1] <= c) {
// 不选和选物品 i 这两种方案的较大值
dp[c] = max(dp[c], dp[c - wgt[i - 1]] + val[i - 1]);
dp[c] = myMax(dp[c], dp[c - wgt[i - 1]] + val[i - 1]);
}
}
}
return dp[cap];
int res = dp[cap];
// 释放内存
free(dp);
return res;
}
/* Driver Code */
@@ -103,10 +112,18 @@ int main() {
printf("不超过背包容量的最大物品价值为 %d\n", res);
// 记忆化搜索
int mem[n + 1][cap + 1];
memset(mem, -1, sizeof(mem));
int **mem = malloc((n + 1) * sizeof(int *));
for (int i = 0; i <= n; i++) {
mem[i] = malloc((cap + 1) * sizeof(int));
memset(mem[i], -1, (cap + 1) * sizeof(int));
}
res = knapsackDFSMem(wgt, val, cap + 1, mem, n, cap);
printf("不超过背包容量的最大物品价值为 %d\n", res);
// 释放内存
for (int i = 0; i <= n; i++) {
free(mem[i]);
}
free(mem);
// 动态规划
res = knapsackDP(wgt, val, cap, wgtSize);

23
codes/c/chapter_dynamic_programming/min_cost_climbing_stairs_dp.c
View File

@@ -7,7 +7,7 @@
#include "../utils/common.h"
/* 求最小值 */
int min(int a, int b) {
int myMin(int a, int b) {
return a < b ? a : b;
}
@@ -17,15 +17,18 @@ int minCostClimbingStairsDP(int cost[], int costSize) {
if (n == 1 || n == 2)
return cost[n];
// 初始化 dp 表，用于存储子问题的解
int dp[n + 1];
int *dp = calloc(n + 1, sizeof(int));
// 初始状态：预设最小子问题的解
dp[1] = cost[1];
dp[2] = cost[2];
// 状态转移：从较小子问题逐步求解较大子问题
for (int i = 3; i <= n; i++) {
dp[i] = min(dp[i - 1], dp[i - 2]) + cost[i];
dp[i] = myMin(dp[i - 1], dp[i - 2]) + cost[i];
}
return dp[n];
int res = dp[n];
// 释放内存
free(dp);
return res;
}
/* 爬楼梯最小代价：空间优化后的动态规划 */
@@ -36,7 +39,7 @@ int minCostClimbingStairsDPComp(int cost[], int costSize) {
int a = cost[1], b = cost[2];
for (int i = 3; i <= n; i++) {
int tmp = b;
b = min(a, tmp) + cost[i];
b = myMin(a, tmp) + cost[i];
a = tmp;
}
return b;
@@ -46,14 +49,8 @@ int minCostClimbingStairsDPComp(int cost[], int costSize) {
int main() {
int cost[] = {0, 1, 10, 1, 1, 1, 10, 1, 1, 10, 1};
int costSize = sizeof(cost) / sizeof(cost[0]);
printf("输入楼梯的代价列表为 [");
for (int i = 0; i < costSize; i++) {
if (i != costSize - 1)
printf("%d, ", cost[i]);
else
printf("%d", cost[i]);
}
printf("]\n");
printf("输入楼梯的代价列表为：");
printArray(cost, costSize);
int res = minCostClimbingStairsDP(cost, costSize);
printf("爬完楼梯的最低代价为 %d\n", res);

62
codes/c/chapter_dynamic_programming/min_path_sum.c
View File

@@ -6,13 +6,16 @@
#include "../utils/common.h"
// 假设矩阵最大行列数为 100
#define MAX_SIZE 100
/* 求最小值 */
int min(int a, int b) {
int myMin(int a, int b) {
return a < b ? a : b;
}
/* 最小路径和：暴力搜索 */
int minPathSumDFS(int gridCols, int grid[][gridCols], int i, int j) {
int minPathSumDFS(int grid[MAX_SIZE][MAX_SIZE], int i, int j) {
// 若为左上角单元格，则终止搜索
if (i == 0 && j == 0) {
return grid[0][0];
@@ -22,14 +25,14 @@ int minPathSumDFS(int gridCols, int grid[][gridCols], int i, int j) {
return INT_MAX;
}
// 计算从左上角到 (i-1, j) 和 (i, j-1) 的最小路径代价
int up = minPathSumDFS(gridCols, grid, i - 1, j);
int left = minPathSumDFS(gridCols, grid, i, j - 1);
int up = minPathSumDFS(grid, i - 1, j);
int left = minPathSumDFS(grid, i, j - 1);
// 返回从左上角到 (i, j) 的最小路径代价
return min(left, up) != INT_MAX ? min(left, up) + grid[i][j] : INT_MAX;
return myMin(left, up) != INT_MAX ? myMin(left, up) + grid[i][j] : INT_MAX;
}
/* 最小路径和：记忆化搜索 */
int minPathSumDFSMem(int gridCols, int grid[][gridCols], int mem[][gridCols], int i, int j) {
int minPathSumDFSMem(int grid[MAX_SIZE][MAX_SIZE], int mem[MAX_SIZE][MAX_SIZE], int i, int j) {
// 若为左上角单元格，则终止搜索
if (i == 0 && j == 0) {
return grid[0][0];
@@ -43,17 +46,20 @@ int minPathSumDFSMem(int gridCols, int grid[][gridCols], int mem[][gridCols], in
return mem[i][j];
}
// 左边和上边单元格的最小路径代价
int up = minPathSumDFSMem(gridCols, grid, mem, i - 1, j);
int left = minPathSumDFSMem(gridCols, grid, mem, i, j - 1);
int up = minPathSumDFSMem(grid, mem, i - 1, j);
int left = minPathSumDFSMem(grid, mem, i, j - 1);
// 记录并返回左上角到 (i, j) 的最小路径代价
mem[i][j] = min(left, up) != INT_MAX ? min(left, up) + grid[i][j] : INT_MAX;
mem[i][j] = myMin(left, up) != INT_MAX ? myMin(left, up) + grid[i][j] : INT_MAX;
return mem[i][j];
}
/* 最小路径和：动态规划 */
int minPathSumDP(int gridCols, int grid[][gridCols], int n, int m) {
int minPathSumDP(int grid[MAX_SIZE][MAX_SIZE], int n, int m) {
// 初始化 dp 表
int dp[n][m];
int **dp = malloc(n * sizeof(int *));
for (int i = 0; i < n; i++) {
dp[i] = calloc(m, sizeof(int));
}
dp[0][0] = grid[0][0];
// 状态转移：首行
for (int j = 1; j < m; j++) {
@@ -66,16 +72,21 @@ int minPathSumDP(int gridCols, int grid[][gridCols], int n, int m) {
// 状态转移：其余行列
for (int i = 1; i < n; i++) {
for (int j = 1; j < m; j++) {
dp[i][j] = min(dp[i][j - 1], dp[i - 1][j]) + grid[i][j];
dp[i][j] = myMin(dp[i][j - 1], dp[i - 1][j]) + grid[i][j];
}
}
return dp[n - 1][m - 1];
int res = dp[n - 1][m - 1];
// 释放内存
for (int i = 0; i < n; i++) {
free(dp[i]);
}
return res;
}
/* 最小路径和：空间优化后的动态规划 */
int minPathSumDPComp(int gridCols, int grid[][gridCols], int n, int m) {
int minPathSumDPComp(int grid[MAX_SIZE][MAX_SIZE], int n, int m) {
// 初始化 dp 表
int dp[m];
int *dp = calloc(m, sizeof(int));
// 状态转移：首行
dp[0] = grid[0][0];
for (int j = 1; j < m; j++) {
@@ -87,33 +98,36 @@ int minPathSumDPComp(int gridCols, int grid[][gridCols], int n, int m) {
dp[0] = dp[0] + grid[i][0];
// 状态转移：其余列
for (int j = 1; j < m; j++) {
dp[j] = min(dp[j - 1], dp[j]) + grid[i][j];
dp[j] = myMin(dp[j - 1], dp[j]) + grid[i][j];
}
}
return dp[m - 1];
int res = dp[m - 1];
// 释放内存
free(dp);
return res;
}
/* Driver Code */
int main() {
int grid[][4] = {{1, 3, 1, 5}, {2, 2, 4, 2}, {5, 3, 2, 1}, {4, 3, 5, 2}};
int n = sizeof(grid) / sizeof(grid[0]), m = sizeof(grid[0]) / sizeof(grid[0][0]);
int grid[MAX_SIZE][MAX_SIZE] = {{1, 3, 1, 5}, {2, 2, 4, 2}, {5, 3, 2, 1}, {4, 3, 5, 2}};
int n = 4, m = 4; // 矩阵容量为 MAX_SIZE * MAX_SIZE ，有效行列数为 n * m
// 暴力搜索
int res = minPathSumDFS(m, grid, n - 1, m - 1);
int res = minPathSumDFS(grid, n - 1, m - 1);
printf("从左上角到右下角的最小路径和为 %d\n", res);
// 记忆化搜索
int mem[n][m];
int mem[MAX_SIZE][MAX_SIZE];
memset(mem, -1, sizeof(mem));
res = minPathSumDFSMem(m, grid, mem, n - 1, m - 1);
res = minPathSumDFSMem(grid, mem, n - 1, m - 1);
printf("从左上角到右下角的最小路径和为 %d\n", res);
// 动态规划
res = minPathSumDP(m, grid, n, m);
res = minPathSumDP(grid, n, m);
printf("从左上角到右下角的最小路径和为 %d\n", res);
// 空间优化后的动态规划
res = minPathSumDPComp(m, grid, n, m);
res = minPathSumDPComp(grid, n, m);
printf("从左上角到右下角的最小路径和为 %d\n", res);
return 0;

27
codes/c/chapter_dynamic_programming/unbounded_knapsack.c
View File

@@ -7,7 +7,7 @@
#include "../utils/common.h"
/* 求最大值 */
int max(int a, int b) {
int myMax(int a, int b) {
return a > b ? a : b;
}
@@ -15,8 +15,10 @@ int max(int a, int b) {
int unboundedKnapsackDP(int wgt[], int val[], int cap, int wgtSize) {
int n = wgtSize;
// 初始化 dp 表
int dp[n + 1][cap + 1];
memset(dp, 0, sizeof(dp));
int **dp = malloc((n + 1) * sizeof(int *));
for (int i = 0; i <= n; i++) {
dp[i] = calloc(cap + 1, sizeof(int));
}
// 状态转移
for (int i = 1; i <= n; i++) {
for (int c = 1; c <= cap; c++) {
@@ -25,19 +27,23 @@ int unboundedKnapsackDP(int wgt[], int val[], int cap, int wgtSize) {
dp[i][c] = dp[i - 1][c];
} else {
// 不选和选物品 i 这两种方案的较大值
dp[i][c] = max(dp[i - 1][c], dp[i][c - wgt[i - 1]] + val[i - 1]);
dp[i][c] = myMax(dp[i - 1][c], dp[i][c - wgt[i - 1]] + val[i - 1]);
}
}
}
return dp[n][cap];
int res = dp[n][cap];
// 释放内存
for (int i = 0; i <= n; i++) {
free(dp[i]);
}
return res;
}
/* 完全背包：空间优化后的动态规划 */
int unboundedKnapsackDPComp(int wgt[], int val[], int cap, int wgtSize) {
int n = wgtSize;
// 初始化 dp 表
int dp[cap + 1];
memset(dp, 0, sizeof(dp));
int *dp = calloc(cap + 1, sizeof(int));
// 状态转移
for (int i = 1; i <= n; i++) {
for (int c = 1; c <= cap; c++) {
@@ -46,11 +52,14 @@ int unboundedKnapsackDPComp(int wgt[], int val[], int cap, int wgtSize) {
dp[c] = dp[c];
} else {
// 不选和选物品 i 这两种方案的较大值
dp[c] = max(dp[c], dp[c - wgt[i - 1]] + val[i - 1]);
dp[c] = myMax(dp[c], dp[c - wgt[i - 1]] + val[i - 1]);
}
}
}
return dp[cap];
int res = dp[cap];
// 释放内存
free(dp);
return res;
}
/* Driver code */