首先,Fletcher 的任何变体都不是 CRC。这是一个校验和。
其次,只要算法正确,您处理的字节数就没有什么特别之处。
第三,您不需要也不应该在每一步都进行模 15。对于速度(与 CRC 相比,这是 Fletcher 和的全部要点),应该有一个仅由sum2 += sum1 += *data++;
. 根据sum1
和sum2
数据类型的大小,您可以计算在溢出之前可以进行多少次迭代,sum2
假设所有输入字节都是0xff
. 然后一个外循环运行该内循环多次,然后是两个模 15。外部循环遍历所有输入数据。
第四,当结束为 15 时,(x >> 4) + (x & 0xf)
操作没有完成预期的操作。需要一个 final 。x % 15
x
if (x == 15) x = 0;
更新:
好的,代码如下:
#include <stdio.h>
#define MAXPART 5803 /* for 32-bit unsigned sum1, sum2 */
/* #define MAXPART 22 for 16-bit unsigned sum1, sum2 */
unsigned fletcher8(unsigned f8, unsigned char *data, size_t len)
{
unsigned long sum1, sum2;
size_t part;
sum1 = f8 & 0xf;
sum2 = (f8 >> 4) & 0xf;
while (len) {
part = len > MAXPART ? MAXPART : len;
len -= part;
do {
sum2 += sum1 += *data++;
} while (--part);
sum1 %= 15;
sum2 %= 15;
}
return (sum2 << 4) + sum1;
}
#define SIZE 131072
int main(void)
{
unsigned f8 = 1;
unsigned char buf[SIZE];
size_t got;
while ((got = fread(buf, 1, SIZE, stdin)) > 0)
f8 = fletcher8(f8, buf, got);
printf("0x%02x\n", f8);
return 0;
}
请注意,我从 Fletcher8 值开始,1
而不是0xff
. 这足以确保任意长度的零字符串将产生相同的零结果。您可以将初始值设置为您喜欢的任何值,只要它不为零即可。
如果机器上的模 ( %
) 运算非常慢,那么% 15
使用一组移位和加法进行运算可能会更快。以下是 32 位类型的示例:
k = (k >> 16) + (k & 0xffff);
k = (k >> 8) + (k & 0xff);
k = (k >> 4) + (k & 0xf);
k = (k >> 4) + (k & 0xf);
if (k > 14)
k -= 15;
对于上述情况len == 17
,代码可以简化为使用unsigned
而不是unsigned long
for sum1
and sum2
,并跳过外循环,因为len <= 22
。非%模运算也可以缩短。就是这样,我还消除了循环中不必要的递减操作:
unsigned fletch8_17(unsigned char *data)
{
unsigned sum1 = 1;
unsigned sum2 = 0;
unsigned char *end = data + 17;
do {
sum2 += sum1 += *data++;
} while (data < end);
sum1 = (sum1 >> 8) + (sum1 & 0xff);
sum1 = (sum1 >> 4) + (sum1 & 0xf);
if (sum1 > 14) {
sum1 -= 15;
if (sum1 > 14)
sum1 -= 15;
}
sum2 = (sum2 >> 8) + (sum2 & 0xff);
sum2 = (sum2 >> 4) + (sum2 & 0xf);
if (sum2 > 14) {
sum2 -= 15;
if (sum2 > 14)
sum2 -= 15;
}
return (sum2 << 4) + sum1;
}
为了比较,你可以试试这个 8 位 CRC,看看它如何比较速度(crc 应该初始化为零):
#include <stddef.h>
/* 8-bit CRC with polynomial x^8+x^6+x^3+x^2+1, 0x14D.
Chosen based on Koopman, et al. (0xA6 in his notation = 0x14D >> 1):
http://www.ece.cmu.edu/~koopman/roses/dsn04/koopman04_crc_poly_embedded.pdf
*/
static unsigned char crc8_table[] = {
0x00, 0x3e, 0x7c, 0x42, 0xf8, 0xc6, 0x84, 0xba, 0x95, 0xab, 0xe9, 0xd7,
0x6d, 0x53, 0x11, 0x2f, 0x4f, 0x71, 0x33, 0x0d, 0xb7, 0x89, 0xcb, 0xf5,
0xda, 0xe4, 0xa6, 0x98, 0x22, 0x1c, 0x5e, 0x60, 0x9e, 0xa0, 0xe2, 0xdc,
0x66, 0x58, 0x1a, 0x24, 0x0b, 0x35, 0x77, 0x49, 0xf3, 0xcd, 0x8f, 0xb1,
0xd1, 0xef, 0xad, 0x93, 0x29, 0x17, 0x55, 0x6b, 0x44, 0x7a, 0x38, 0x06,
0xbc, 0x82, 0xc0, 0xfe, 0x59, 0x67, 0x25, 0x1b, 0xa1, 0x9f, 0xdd, 0xe3,
0xcc, 0xf2, 0xb0, 0x8e, 0x34, 0x0a, 0x48, 0x76, 0x16, 0x28, 0x6a, 0x54,
0xee, 0xd0, 0x92, 0xac, 0x83, 0xbd, 0xff, 0xc1, 0x7b, 0x45, 0x07, 0x39,
0xc7, 0xf9, 0xbb, 0x85, 0x3f, 0x01, 0x43, 0x7d, 0x52, 0x6c, 0x2e, 0x10,
0xaa, 0x94, 0xd6, 0xe8, 0x88, 0xb6, 0xf4, 0xca, 0x70, 0x4e, 0x0c, 0x32,
0x1d, 0x23, 0x61, 0x5f, 0xe5, 0xdb, 0x99, 0xa7, 0xb2, 0x8c, 0xce, 0xf0,
0x4a, 0x74, 0x36, 0x08, 0x27, 0x19, 0x5b, 0x65, 0xdf, 0xe1, 0xa3, 0x9d,
0xfd, 0xc3, 0x81, 0xbf, 0x05, 0x3b, 0x79, 0x47, 0x68, 0x56, 0x14, 0x2a,
0x90, 0xae, 0xec, 0xd2, 0x2c, 0x12, 0x50, 0x6e, 0xd4, 0xea, 0xa8, 0x96,
0xb9, 0x87, 0xc5, 0xfb, 0x41, 0x7f, 0x3d, 0x03, 0x63, 0x5d, 0x1f, 0x21,
0x9b, 0xa5, 0xe7, 0xd9, 0xf6, 0xc8, 0x8a, 0xb4, 0x0e, 0x30, 0x72, 0x4c,
0xeb, 0xd5, 0x97, 0xa9, 0x13, 0x2d, 0x6f, 0x51, 0x7e, 0x40, 0x02, 0x3c,
0x86, 0xb8, 0xfa, 0xc4, 0xa4, 0x9a, 0xd8, 0xe6, 0x5c, 0x62, 0x20, 0x1e,
0x31, 0x0f, 0x4d, 0x73, 0xc9, 0xf7, 0xb5, 0x8b, 0x75, 0x4b, 0x09, 0x37,
0x8d, 0xb3, 0xf1, 0xcf, 0xe0, 0xde, 0x9c, 0xa2, 0x18, 0x26, 0x64, 0x5a,
0x3a, 0x04, 0x46, 0x78, 0xc2, 0xfc, 0xbe, 0x80, 0xaf, 0x91, 0xd3, 0xed,
0x57, 0x69, 0x2b, 0x15};
unsigned crc8(unsigned crc, unsigned char *data, size_t len)
{
unsigned char *end;
if (len == 0)
return crc;
crc ^= 0xff;
end = data + len;
do {
crc = crc8_table[crc ^ *data++];
} while (data < end);
return crc ^ 0xff;
}
8 位 CRC 肯定会比 8 位 Fletcher 校验和提供更好的错误检测性能。在这种情况下,它甚至可能更快!