In computer science, the Raita algorithm is a string searching algorithm which improves the performance of Boyer–Moore–Horspool algorithm. This algorithm preprocesses the string being searched for the pattern, which is similar to Boyer–Moore string-search algorithm. The searching pattern of particular sub-string in a given string is different from Boyer–Moore–Horspool algorithm. This algorithm was published by Timo Raita in 1991.[1]
Raita algorithm searches for a pattern "P" in a given text "T" by comparing each character of pattern in the given text. Searching will be done as follows. Window for a text "T" is defined as the length of "P".
If everything in the pre-check is successful, then the original comparison starts from the second character to last but one. If there is a mismatch at any stage in the algorithm, it performs the bad character shift function which was computed in pre-processing phase. Bad character shift function is identical to the one proposed in Boyer–Moore–Horspool algorithm.[1]
A modern formulation of a similar pre-check is found in std::string::find, a linear/quadratic string-matcher, in libc++ and libstdc++. Assuming a well-optimized version of memcmp, not skipping characters in the "original comparison" tends to be more efficient as the pattern is likely to be aligned.[2]
std::string::find
memcmp
#include <limits.h> #include <stddef.h> #define ALPHABET_SIZE (1 << CHAR_BITS) /* typically 256 */ /* Preprocessing: the BMH bad-match table. */ static inline void preBmBc(char *pat, size_t lpat, ptrdiff_t bmBc[]) { size_t i; for (i = 0; i < ALPHABET_SIZE; ++i) bmBc[i] = lpat; for (i = 0; i < lpat - 1; ++i) bmBc[pat[i]] = lpat - i - 1; } void RAITA(char *pat, size_t lpat, char *s, size_t n) { ptrdiff_t bmBc[ALPHABET_SIZE]; /* Quick edge cases. */ if (lpat == 0 || lpat > n) return; if (lpat == 1) { char *match_ptr = s; while (match_ptr < s + n) { match_ptr = memchr(match_ptr, pat[0], n - (match_ptr - s)); if (match_ptr != NULL) { OUTPUT(match_ptr - s); match_ptr++; } else return; } } preBmBc(pat, lpat, bmBc); /* The prematch-window. */ char firstCh = pat[0]; char middleCh = pat[lpat / 2]; char lastCh = pat[lpat - 1]; /* Searching */ ptrdiff_t j = 0; while (j <= n - m) { char c = s[j + lpat - 1]; /* This could harm data locality on long patterns. For these consider reducing * the number of pre-tests, or using more clustered indices. */ if (lastCh == c && middleCh == s[j + lpat / 2] && firstCh == s[j] && memcmp(&pat[1], &s[j+1], lpat - 2) == 0) OUTPUT(j); j += bmBc[c]; } }
Pattern: abddb
Text:abbaabaabddbabadbb
Pre- Processing stage:
a b d 4 3 1
Attempt 1: abbaabaabddbabadbb ....b Shift by 4 (bmBc[a])
Comparison of last character of pattern to rightmost character in the window. It's a mismatch and shifted by 4 according to the value in pre-processing stage.
Attempt 2: abbaabaabddbabadbb A.d.B Shift by 3 (bmBc[b])
Here last and first character of the pattern are matched but middle character is a mismatch. So the pattern is shifted according to the pre-processing stage.
Attempt 3: abbaabaabddbabadbb ABDDB Shift by 3 (bmBc[b])
We found exact match here but the algorithm continues until it can't move further.
Attempt 4: abbaabaABDDBabadbb ....b Shift by 4 (bmBc[a])
At this stage, we need to shift by 4 and we can't move the pattern by 4. So, the algorithm terminates. Letters in capital letter are exact match of the pattern in the text.