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/*
** 2011 March 24
**
** The author disclaims copyright to this source code. In place of
** a legal notice, here is a blessing:
**
** May you do good and not evil.
** May you find forgiveness for yourself and forgive others.
** May you share freely, never taking more than you give.
**
*************************************************************************
**
** Code for a demonstration virtual table that generates variations
** on an input word at increasing edit distances from the original.
**
** A fuzzer virtual table is created like this:
**
** CREATE VIRTUAL TABLE f USING fuzzer(<fuzzer-data-table>);
**
** When it is created, the new fuzzer table must be supplied with the
** name of a "fuzzer data table", which must reside in the same database
** file as the new fuzzer table. The fuzzer data table contains the various
** transformations and their costs that the fuzzer logic uses to generate
** variations.
**
** The fuzzer data table must contain exactly four columns (more precisely,
** the statement "SELECT * FROM <fuzzer_data_table>" must return records
** that consist of four columns). It does not matter what the columns are
** named.
**
** Each row in the fuzzer data table represents a single character
** transformation. The left most column of the row (column 0) contains an
** integer value - the identifier of the ruleset to which the transformation
** rule belongs (see "MULTIPLE RULE SETS" below). The second column of the
** row (column 0) contains the input character or characters. The third
** column contains the output character or characters. And the fourth column
** contains the integer cost of making the transformation. For example:
**
** CREATE TABLE f_data(ruleset, cFrom, cTo, Cost);
** INSERT INTO f_data(ruleset, cFrom, cTo, Cost) VALUES(0, '', 'a', 100);
** INSERT INTO f_data(ruleset, cFrom, cTo, Cost) VALUES(0, 'b', '', 87);
** INSERT INTO f_data(ruleset, cFrom, cTo, Cost) VALUES(0, 'o', 'oe', 38);
** INSERT INTO f_data(ruleset, cFrom, cTo, Cost) VALUES(0, 'oe', 'o', 40);
**
** The first row inserted into the fuzzer data table by the SQL script
** above indicates that the cost of inserting a letter 'a' is 100. (All
** costs are integers. We recommend that costs be scaled so that the
** average cost is around 100.) The second INSERT statement creates a rule
** saying that the cost of deleting a single letter 'b' is 87. The third
** and fourth INSERT statements mean that the cost of transforming a
** single letter "o" into the two-letter sequence "oe" is 38 and that the
** cost of transforming "oe" back into "o" is 40.
**
** The contents of the fuzzer data table are loaded into main memory when
** a fuzzer table is first created, and may be internally reloaded by the
** system at any subsequent time. Therefore, the fuzzer data table should be
** populated before the fuzzer table is created and not modified thereafter.
** If you do need to modify the contents of the fuzzer data table, it is
** recommended that the associated fuzzer table be dropped, the fuzzer data
** table edited, and the fuzzer table recreated within a single transaction.
** Alternatively, the fuzzer data table can be edited then the database
** connection can be closed and reopened.
**
** Once it has been created, the fuzzer table can be queried as follows:
**
** SELECT word, distance FROM f
** WHERE word MATCH 'abcdefg'
** AND distance<200;
**
** This first query outputs the string "abcdefg" and all strings that
** can be derived from that string by appling the specified transformations.
** The strings are output together with their total transformation cost
** (called "distance") and appear in order of increasing cost. No string
** is output more than once. If there are multiple ways to transform the
** target string into the output string then the lowest cost transform is
** the one that is returned. In the example, the search is limited to
** strings with a total distance of less than 200.
**
** The fuzzer is a read-only table. Any attempt to DELETE, INSERT, or
** UPDATE on a fuzzer table will throw an error.
**
** It is important to put some kind of a limit on the fuzzer output. This
** can be either in the form of a LIMIT clause at the end of the query,
** or better, a "distance<NNN" constraint where NNN is some number. The
** running time and memory requirement is exponential in the value of NNN
** so you want to make sure that NNN is not too big. A value of NNN that
** is about twice the average transformation cost seems to give good results.
**
** The fuzzer table can be useful for tasks such as spelling correction.
** Suppose there is a second table vocabulary(w) where the w column contains
** all correctly spelled words. Let $word be a word you want to look up.
**
** SELECT vocabulary.w FROM f, vocabulary
** WHERE f.word MATCH $word
** AND f.distance<=200
** AND f.word=vocabulary.w
** LIMIT 20
**
** The query above gives the 20 closest words to the $word being tested.
** (Note that for good performance, the vocubulary.w column should be
** indexed.)
**
** A similar query can be used to find all words in the dictionary that
** begin with some prefix $prefix:
**
** SELECT vocabulary.w FROM f, vocabulary
** WHERE f.word MATCH $prefix
** AND f.distance<=200
** AND vocabulary.w BETWEEN f.word AND (f.word || x'F7BFBFBF')
** LIMIT 50
**
** This last query will show up to 50 words out of the vocabulary that
** match or nearly match the $prefix.
**
** MULTIPLE RULE SETS
**
** Normally, the "ruleset" value associated with all character transformations
** in the fuzzer data table is zero. However, if required, the fuzzer table
** allows multiple rulesets to be defined. Each query uses only a single
** ruleset. This allows, for example, a single fuzzer table to support
** multiple languages.
**
** By default, only the rules from ruleset 0 are used. To specify an
** alternative ruleset, a "ruleset = ?" expression must be added to the
** WHERE clause of a SELECT, where ? is the identifier of the desired
** ruleset. For example:
**
** SELECT vocabulary.w FROM f, vocabulary
** WHERE f.word MATCH $word
** AND f.distance<=200
** AND f.word=vocabulary.w
** AND f.ruleset=1 -- Specify the ruleset to use here
** LIMIT 20
**
** If no "ruleset = ?" constraint is specified in the WHERE clause, ruleset
** 0 is used.
**
** LIMITS
**
** The maximum ruleset number is 2147483647. The maximum length of either
** of the strings in the second or third column of the fuzzer data table
** is 50 bytes. The maximum cost on a rule is 1000.
*/
#include "sqlite3ext.h"
SQLITE_EXTENSION_INIT1
/* If SQLITE_DEBUG is not defined, disable assert statements. */
#if !defined(NDEBUG) && !defined(SQLITE_DEBUG)
# define NDEBUG
#endif
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <stdio.h>
#ifndef SQLITE_OMIT_VIRTUALTABLE
/*
** Forward declaration of objects used by this implementation
*/
typedef struct fuzzer_vtab fuzzer_vtab;
typedef struct fuzzer_cursor fuzzer_cursor;
typedef struct fuzzer_rule fuzzer_rule;
typedef struct fuzzer_seen fuzzer_seen;
typedef struct fuzzer_stem fuzzer_stem;
/*
** Various types.
**
** fuzzer_cost is the "cost" of an edit operation.
**
** fuzzer_len is the length of a matching string.
**
** fuzzer_ruleid is an ruleset identifier.
*/
typedef int fuzzer_cost;
typedef signed char fuzzer_len;
typedef int fuzzer_ruleid;
/*
** Limits
*/
#define FUZZER_MX_LENGTH 50 /* Maximum length of a rule string */
#define FUZZER_MX_RULEID 2147483647 /* Maximum rule ID */
#define FUZZER_MX_COST 1000 /* Maximum single-rule cost */
#define FUZZER_MX_OUTPUT_LENGTH 100 /* Maximum length of an output string */
/*
** Each transformation rule is stored as an instance of this object.
** All rules are kept on a linked list sorted by rCost.
*/
struct fuzzer_rule {
fuzzer_rule *pNext; /* Next rule in order of increasing rCost */
char *zFrom; /* Transform from */
fuzzer_cost rCost; /* Cost of this transformation */
fuzzer_len nFrom, nTo; /* Length of the zFrom and zTo strings */
fuzzer_ruleid iRuleset; /* The rule set to which this rule belongs */
char zTo[4]; /* Transform to (extra space appended) */
};
/*
** A stem object is used to generate variants. It is also used to record
** previously generated outputs.
**
** Every stem is added to a hash table as it is output. Generation of
** duplicate stems is suppressed.
**
** Active stems (those that might generate new outputs) are kepts on a linked
** list sorted by increasing cost. The cost is the sum of rBaseCost and
** pRule->rCost.
*/
struct fuzzer_stem {
char *zBasis; /* Word being fuzzed */
const fuzzer_rule *pRule; /* Current rule to apply */
fuzzer_stem *pNext; /* Next stem in rCost order */
fuzzer_stem *pHash; /* Next stem with same hash on zBasis */
fuzzer_cost rBaseCost; /* Base cost of getting to zBasis */
fuzzer_cost rCostX; /* Precomputed rBaseCost + pRule->rCost */
fuzzer_len nBasis; /* Length of the zBasis string */
fuzzer_len n; /* Apply pRule at this character offset */
};
/*
** A fuzzer virtual-table object
*/
struct fuzzer_vtab {
sqlite3_vtab base; /* Base class - must be first */
char *zClassName; /* Name of this class. Default: "fuzzer" */
fuzzer_rule *pRule; /* All active rules in this fuzzer */
int nCursor; /* Number of active cursors */
};
#define FUZZER_HASH 4001 /* Hash table size */
#define FUZZER_NQUEUE 20 /* Number of slots on the stem queue */
/* A fuzzer cursor object */
struct fuzzer_cursor {
sqlite3_vtab_cursor base; /* Base class - must be first */
sqlite3_int64 iRowid; /* The rowid of the current word */
fuzzer_vtab *pVtab; /* The virtual table this cursor belongs to */
fuzzer_cost rLimit; /* Maximum cost of any term */
fuzzer_stem *pStem; /* Stem with smallest rCostX */
fuzzer_stem *pDone; /* Stems already processed to completion */
fuzzer_stem *aQueue[FUZZER_NQUEUE]; /* Queue of stems with higher rCostX */
int mxQueue; /* Largest used index in aQueue[] */
char *zBuf; /* Temporary use buffer */
int nBuf; /* Bytes allocated for zBuf */
int nStem; /* Number of stems allocated */
int iRuleset; /* Only process rules from this ruleset */
fuzzer_rule nullRule; /* Null rule used first */
fuzzer_stem *apHash[FUZZER_HASH]; /* Hash of previously generated terms */
};
/*
** The two input rule lists are both sorted in order of increasing
** cost. Merge them together into a single list, sorted by cost, and
** return a pointer to the head of that list.
*/
static fuzzer_rule *fuzzerMergeRules(fuzzer_rule *pA, fuzzer_rule *pB){
fuzzer_rule head;
fuzzer_rule *pTail;
pTail = &head;
while( pA && pB ){
if( pA->rCost<=pB->rCost ){
pTail->pNext = pA;
pTail = pA;
pA = pA->pNext;
}else{
pTail->pNext = pB;
pTail = pB;
pB = pB->pNext;
}
}
if( pA==0 ){
pTail->pNext = pB;
}else{
pTail->pNext = pA;
}
return head.pNext;
}
/*
** Statement pStmt currently points to a row in the fuzzer data table. This
** function allocates and populates a fuzzer_rule structure according to
** the content of the row.
**
** If successful, *ppRule is set to point to the new object and SQLITE_OK
** is returned. Otherwise, *ppRule is zeroed, *pzErr may be set to point
** to an error message and an SQLite error code returned.
*/
static int fuzzerLoadOneRule(
fuzzer_vtab *p, /* Fuzzer virtual table handle */
sqlite3_stmt *pStmt, /* Base rule on statements current row */
fuzzer_rule **ppRule, /* OUT: New rule object */
char **pzErr /* OUT: Error message */
){
sqlite3_int64 iRuleset = sqlite3_column_int64(pStmt, 0);
const char *zFrom = (const char *)sqlite3_column_text(pStmt, 1);
const char *zTo = (const char *)sqlite3_column_text(pStmt, 2);
int nCost = sqlite3_column_int(pStmt, 3);
int rc = SQLITE_OK; /* Return code */
int nFrom; /* Size of string zFrom, in bytes */
int nTo; /* Size of string zTo, in bytes */
fuzzer_rule *pRule = 0; /* New rule object to return */
if( zFrom==0 ) zFrom = "";
if( zTo==0 ) zTo = "";
nFrom = (int)strlen(zFrom);
nTo = (int)strlen(zTo);
/* Silently ignore null transformations */
if( strcmp(zFrom, zTo)==0 ){
*ppRule = 0;
return SQLITE_OK;
}
if( nCost<=0 || nCost>FUZZER_MX_COST ){
*pzErr = sqlite3_mprintf("%s: cost must be between 1 and %d",
p->zClassName, FUZZER_MX_COST
);
rc = SQLITE_ERROR;
}else
if( nFrom>FUZZER_MX_LENGTH || nTo>FUZZER_MX_LENGTH ){
*pzErr = sqlite3_mprintf("%s: maximum string length is %d",
p->zClassName, FUZZER_MX_LENGTH
);
rc = SQLITE_ERROR;
}else
if( iRuleset<0 || iRuleset>FUZZER_MX_RULEID ){
*pzErr = sqlite3_mprintf("%s: ruleset must be between 0 and %d",
p->zClassName, FUZZER_MX_RULEID
);
rc = SQLITE_ERROR;
}else{
pRule = sqlite3_malloc64( sizeof(*pRule) + nFrom + nTo );
if( pRule==0 ){
rc = SQLITE_NOMEM;
}else{
memset(pRule, 0, sizeof(*pRule));
pRule->zFrom = pRule->zTo;
pRule->zFrom += nTo + 1;
pRule->nFrom = (fuzzer_len)nFrom;
memcpy(pRule->zFrom, zFrom, nFrom+1);
memcpy(pRule->zTo, zTo, nTo+1);
pRule->nTo = (fuzzer_len)nTo;
pRule->rCost = nCost;
pRule->iRuleset = (int)iRuleset;
}
}
*ppRule = pRule;
return rc;
}
/*
** Load the content of the fuzzer data table into memory.
*/
static int fuzzerLoadRules(
sqlite3 *db, /* Database handle */
fuzzer_vtab *p, /* Virtual fuzzer table to configure */
const char *zDb, /* Database containing rules data */
const char *zData, /* Table containing rules data */
char **pzErr /* OUT: Error message */
){
int rc = SQLITE_OK; /* Return code */
char *zSql; /* SELECT used to read from rules table */
fuzzer_rule *pHead = 0;
zSql = sqlite3_mprintf("SELECT * FROM %Q.%Q", zDb, zData);
if( zSql==0 ){
rc = SQLITE_NOMEM;
}else{
int rc2; /* finalize() return code */
sqlite3_stmt *pStmt = 0;
rc = sqlite3_prepare_v2(db, zSql, -1, &pStmt, 0);
if( rc!=SQLITE_OK ){
*pzErr = sqlite3_mprintf("%s: %s", p->zClassName, sqlite3_errmsg(db));
}else if( sqlite3_column_count(pStmt)!=4 ){
*pzErr = sqlite3_mprintf("%s: %s has %d columns, expected 4",
p->zClassName, zData, sqlite3_column_count(pStmt)
);
rc = SQLITE_ERROR;
}else{
while( rc==SQLITE_OK && SQLITE_ROW==sqlite3_step(pStmt) ){
fuzzer_rule *pRule = 0;
rc = fuzzerLoadOneRule(p, pStmt, &pRule, pzErr);
if( pRule ){
pRule->pNext = pHead;
pHead = pRule;
}
}
}
rc2 = sqlite3_finalize(pStmt);
if( rc==SQLITE_OK ) rc = rc2;
}
sqlite3_free(zSql);
/* All rules are now in a singly linked list starting at pHead. This
** block sorts them by cost and then sets fuzzer_vtab.pRule to point to
** point to the head of the sorted list.
*/
if( rc==SQLITE_OK ){
unsigned int i;
fuzzer_rule *pX;
fuzzer_rule *a[15];
for(i=0; i<sizeof(a)/sizeof(a[0]); i++) a[i] = 0;
while( (pX = pHead)!=0 ){
pHead = pX->pNext;
pX->pNext = 0;
for(i=0; a[i] && i<sizeof(a)/sizeof(a[0])-1; i++){
pX = fuzzerMergeRules(a[i], pX);
a[i] = 0;
}
a[i] = fuzzerMergeRules(a[i], pX);
}
for(pX=a[0], i=1; i<sizeof(a)/sizeof(a[0]); i++){
pX = fuzzerMergeRules(a[i], pX);
}
p->pRule = fuzzerMergeRules(p->pRule, pX);
}else{
/* An error has occurred. Setting p->pRule to point to the head of the
** allocated list ensures that the list will be cleaned up in this case.
*/
assert( p->pRule==0 );
p->pRule = pHead;
}
return rc;
}
/*
** This function converts an SQL quoted string into an unquoted string
** and returns a pointer to a buffer allocated using sqlite3_malloc()
** containing the result. The caller should eventually free this buffer
** using sqlite3_free.
**
** Examples:
**
** "abc" becomes abc
** 'xyz' becomes xyz
** [pqr] becomes pqr
** `mno` becomes mno
*/
static char *fuzzerDequote(const char *zIn){
sqlite3_int64 nIn; /* Size of input string, in bytes */
char *zOut; /* Output (dequoted) string */
nIn = strlen(zIn);
zOut = sqlite3_malloc64(nIn+1);
if( zOut ){
char q = zIn[0]; /* Quote character (if any ) */
if( q!='[' && q!= '\'' && q!='"' && q!='`' ){
memcpy(zOut, zIn, (size_t)(nIn+1));
}else{
int iOut = 0; /* Index of next byte to write to output */
int iIn; /* Index of next byte to read from input */
if( q=='[' ) q = ']';
for(iIn=1; iIn<nIn; iIn++){
if( zIn[iIn]==q ) iIn++;
zOut[iOut++] = zIn[iIn];
}
}
assert( (int)strlen(zOut)<=nIn );
}
return zOut;
}
/*
** xDisconnect/xDestroy method for the fuzzer module.
*/
static int fuzzerDisconnect(sqlite3_vtab *pVtab){
fuzzer_vtab *p = (fuzzer_vtab*)pVtab;
assert( p->nCursor==0 );
while( p->pRule ){
fuzzer_rule *pRule = p->pRule;
p->pRule = pRule->pNext;
sqlite3_free(pRule);
}
sqlite3_free(p);
return SQLITE_OK;
}
/*
** xConnect/xCreate method for the fuzzer module. Arguments are:
**
** argv[0] -> module name ("fuzzer")
** argv[1] -> database name
** argv[2] -> table name
** argv[3] -> fuzzer rule table name
*/
static int fuzzerConnect(
sqlite3 *db,
void *pAux,
int argc, const char *const*argv,
sqlite3_vtab **ppVtab,
char **pzErr
){
int rc = SQLITE_OK; /* Return code */
fuzzer_vtab *pNew = 0; /* New virtual table */
const char *zModule = argv[0];
const char *zDb = argv[1];
if( argc!=4 ){
*pzErr = sqlite3_mprintf(
"%s: wrong number of CREATE VIRTUAL TABLE arguments", zModule
);
rc = SQLITE_ERROR;
}else{
sqlite3_int64 nModule; /* Length of zModule, in bytes */
nModule = strlen(zModule);
pNew = sqlite3_malloc64( sizeof(*pNew) + nModule + 1);
if( pNew==0 ){
rc = SQLITE_NOMEM;
}else{
char *zTab; /* Dequoted name of fuzzer data table */
memset(pNew, 0, sizeof(*pNew));
pNew->zClassName = (char*)&pNew[1];
memcpy(pNew->zClassName, zModule, (size_t)(nModule+1));
zTab = fuzzerDequote(argv[3]);
if( zTab==0 ){
rc = SQLITE_NOMEM;
}else{
rc = fuzzerLoadRules(db, pNew, zDb, zTab, pzErr);
sqlite3_free(zTab);
}
if( rc==SQLITE_OK ){
rc = sqlite3_declare_vtab(db, "CREATE TABLE x(word,distance,ruleset)");
}
if( rc!=SQLITE_OK ){
fuzzerDisconnect((sqlite3_vtab *)pNew);
pNew = 0;
}else{
sqlite3_vtab_config(db, SQLITE_VTAB_INNOCUOUS);
}
}
}
*ppVtab = (sqlite3_vtab *)pNew;
return rc;
}
/*
** Open a new fuzzer cursor.
*/
static int fuzzerOpen(sqlite3_vtab *pVTab, sqlite3_vtab_cursor **ppCursor){
fuzzer_vtab *p = (fuzzer_vtab*)pVTab;
fuzzer_cursor *pCur;
pCur = sqlite3_malloc( sizeof(*pCur) );
if( pCur==0 ) return SQLITE_NOMEM;
memset(pCur, 0, sizeof(*pCur));
pCur->pVtab = p;
*ppCursor = &pCur->base;
p->nCursor++;
return SQLITE_OK;
}
/*
** Free all stems in a list.
*/
static void fuzzerClearStemList(fuzzer_stem *pStem){
while( pStem ){
fuzzer_stem *pNext = pStem->pNext;
sqlite3_free(pStem);
pStem = pNext;
}
}
/*
** Free up all the memory allocated by a cursor. Set it rLimit to 0
** to indicate that it is at EOF.
*/
static void fuzzerClearCursor(fuzzer_cursor *pCur, int clearHash){
int i;
fuzzerClearStemList(pCur->pStem);
fuzzerClearStemList(pCur->pDone);
for(i=0; i<FUZZER_NQUEUE; i++) fuzzerClearStemList(pCur->aQueue[i]);
pCur->rLimit = (fuzzer_cost)0;
if( clearHash && pCur->nStem ){
pCur->mxQueue = 0;
pCur->pStem = 0;
pCur->pDone = 0;
memset(pCur->aQueue, 0, sizeof(pCur->aQueue));
memset(pCur->apHash, 0, sizeof(pCur->apHash));
}
pCur->nStem = 0;
}
/*
** Close a fuzzer cursor.
*/
static int fuzzerClose(sqlite3_vtab_cursor *cur){
fuzzer_cursor *pCur = (fuzzer_cursor *)cur;
fuzzerClearCursor(pCur, 0);
sqlite3_free(pCur->zBuf);
pCur->pVtab->nCursor--;
sqlite3_free(pCur);
return SQLITE_OK;
}
/*
** Compute the current output term for a fuzzer_stem.
*/
static int fuzzerRender(
fuzzer_stem *pStem, /* The stem to be rendered */
char **pzBuf, /* Write results into this buffer. realloc if needed */
int *pnBuf /* Size of the buffer */
){
const fuzzer_rule *pRule = pStem->pRule;
int n; /* Size of output term without nul-term */
char *z; /* Buffer to assemble output term in */
n = pStem->nBasis + pRule->nTo - pRule->nFrom;
if( (*pnBuf)<n+1 ){
(*pzBuf) = sqlite3_realloc((*pzBuf), n+100);
if( (*pzBuf)==0 ) return SQLITE_NOMEM;
(*pnBuf) = n+100;
}
n = pStem->n;
z = *pzBuf;
if( n<0 ){
memcpy(z, pStem->zBasis, pStem->nBasis+1);
}else{
memcpy(z, pStem->zBasis, n);
memcpy(&z[n], pRule->zTo, pRule->nTo);
memcpy(&z[n+pRule->nTo], &pStem->zBasis[n+pRule->nFrom],
pStem->nBasis-n-pRule->nFrom+1);
}
assert( z[pStem->nBasis + pRule->nTo - pRule->nFrom]==0 );
return SQLITE_OK;
}
/*
** Compute a hash on zBasis.
*/
static unsigned int fuzzerHash(const char *z){
unsigned int h = 0;
while( *z ){ h = (h<<3) ^ (h>>29) ^ *(z++); }
return h % FUZZER_HASH;
}
/*
** Current cost of a stem
*/
static fuzzer_cost fuzzerCost(fuzzer_stem *pStem){
return pStem->rCostX = pStem->rBaseCost + pStem->pRule->rCost;
}
#if 0
/*
** Print a description of a fuzzer_stem on stderr.
*/
static void fuzzerStemPrint(
const char *zPrefix,
fuzzer_stem *pStem,
const char *zSuffix
){
if( pStem->n<0 ){
fprintf(stderr, "%s[%s](%d)-->self%s",
zPrefix,
pStem->zBasis, pStem->rBaseCost,
zSuffix
);
}else{
char *zBuf = 0;
int nBuf = 0;
if( fuzzerRender(pStem, &zBuf, &nBuf)!=SQLITE_OK ) return;
fprintf(stderr, "%s[%s](%d)-->{%s}(%d)%s",
zPrefix,
pStem->zBasis, pStem->rBaseCost, zBuf, pStem->,
zSuffix
);
sqlite3_free(zBuf);
}
}
#endif
/*
** Return 1 if the string to which the cursor is point has already
** been emitted. Return 0 if not. Return -1 on a memory allocation
** failures.
*/
static int fuzzerSeen(fuzzer_cursor *pCur, fuzzer_stem *pStem){
unsigned int h;
fuzzer_stem *pLookup;
if( fuzzerRender(pStem, &pCur->zBuf, &pCur->nBuf)==SQLITE_NOMEM ){
return -1;
}
h = fuzzerHash(pCur->zBuf);
pLookup = pCur->apHash[h];
while( pLookup && strcmp(pLookup->zBasis, pCur->zBuf)!=0 ){
pLookup = pLookup->pHash;
}
return pLookup!=0;
}
/*
** If argument pRule is NULL, this function returns false.
**
** Otherwise, it returns true if rule pRule should be skipped. A rule
** should be skipped if it does not belong to rule-set iRuleset, or if
** applying it to stem pStem would create a string longer than
** FUZZER_MX_OUTPUT_LENGTH bytes.
*/
static int fuzzerSkipRule(
const fuzzer_rule *pRule, /* Determine whether or not to skip this */
fuzzer_stem *pStem, /* Stem rule may be applied to */
int iRuleset /* Rule-set used by the current query */
){
return pRule && (
(pRule->iRuleset!=iRuleset)
|| (pStem->nBasis + pRule->nTo - pRule->nFrom)>FUZZER_MX_OUTPUT_LENGTH
);
}
/*
** Advance a fuzzer_stem to its next value. Return 0 if there are
** no more values that can be generated by this fuzzer_stem. Return
** -1 on a memory allocation failure.
*/
static int fuzzerAdvance(fuzzer_cursor *pCur, fuzzer_stem *pStem){
const fuzzer_rule *pRule;
while( (pRule = pStem->pRule)!=0 ){
assert( pRule==&pCur->nullRule || pRule->iRuleset==pCur->iRuleset );
while( pStem->n < pStem->nBasis - pRule->nFrom ){
pStem->n++;
if( pRule->nFrom==0
|| memcmp(&pStem->zBasis[pStem->n], pRule->zFrom, pRule->nFrom)==0
){
/* Found a rewrite case. Make sure it is not a duplicate */
int rc = fuzzerSeen(pCur, pStem);
if( rc<0 ) return -1;
if( rc==0 ){
fuzzerCost(pStem);
return 1;
}
}
}
pStem->n = -1;
do{
pRule = pRule->pNext;
}while( fuzzerSkipRule(pRule, pStem, pCur->iRuleset) );
pStem->pRule = pRule;
if( pRule && fuzzerCost(pStem)>pCur->rLimit ) pStem->pRule = 0;
}
return 0;
}
/*
** The two input stem lists are both sorted in order of increasing
** rCostX. Merge them together into a single list, sorted by rCostX, and
** return a pointer to the head of that new list.
*/
static fuzzer_stem *fuzzerMergeStems(fuzzer_stem *pA, fuzzer_stem *pB){
fuzzer_stem head;
fuzzer_stem *pTail;
pTail = &head;
while( pA && pB ){
if( pA->rCostX<=pB->rCostX ){
pTail->pNext = pA;
pTail = pA;
pA = pA->pNext;
}else{
pTail->pNext = pB;
pTail = pB;
pB = pB->pNext;
}
}
if( pA==0 ){
pTail->pNext = pB;
}else{
pTail->pNext = pA;
}
return head.pNext;
}
/*
** Load pCur->pStem with the lowest-cost stem. Return a pointer
** to the lowest-cost stem.
*/
static fuzzer_stem *fuzzerLowestCostStem(fuzzer_cursor *pCur){
fuzzer_stem *pBest, *pX;
int iBest;
int i;
if( pCur->pStem==0 ){
iBest = -1;
pBest = 0;
for(i=0; i<=pCur->mxQueue; i++){
pX = pCur->aQueue[i];
if( pX==0 ) continue;
if( pBest==0 || pBest->rCostX>pX->rCostX ){
pBest = pX;
iBest = i;
}
}
if( pBest ){
pCur->aQueue[iBest] = pBest->pNext;
pBest->pNext = 0;
pCur->pStem = pBest;
}
}
return pCur->pStem;
}
/*
** Insert pNew into queue of pending stems. Then find the stem
** with the lowest rCostX and move it into pCur->pStem.
** list. The insert is done such the pNew is in the correct order
** according to fuzzer_stem.zBaseCost+fuzzer_stem.pRule->rCost.
*/
static fuzzer_stem *fuzzerInsert(fuzzer_cursor *pCur, fuzzer_stem *pNew){
fuzzer_stem *pX;
int i;
/* If pCur->pStem exists and is greater than pNew, then make pNew
** the new pCur->pStem and insert the old pCur->pStem instead.
*/
if( (pX = pCur->pStem)!=0 && pX->rCostX>pNew->rCostX ){
pNew->pNext = 0;
pCur->pStem = pNew;
pNew = pX;
}
/* Insert the new value */
pNew->pNext = 0;
pX = pNew;
for(i=0; i<=pCur->mxQueue; i++){
if( pCur->aQueue[i] ){
pX = fuzzerMergeStems(pX, pCur->aQueue[i]);
pCur->aQueue[i] = 0;
}else{
pCur->aQueue[i] = pX;
break;
}
}
if( i>pCur->mxQueue ){
if( i<FUZZER_NQUEUE ){
pCur->mxQueue = i;
pCur->aQueue[i] = pX;
}else{
assert( pCur->mxQueue==FUZZER_NQUEUE-1 );
pX = fuzzerMergeStems(pX, pCur->aQueue[FUZZER_NQUEUE-1]);
pCur->aQueue[FUZZER_NQUEUE-1] = pX;
}
}
return fuzzerLowestCostStem(pCur);
}
/*
** Allocate a new fuzzer_stem. Add it to the hash table but do not
** link it into either the pCur->pStem or pCur->pDone lists.
*/
static fuzzer_stem *fuzzerNewStem(
fuzzer_cursor *pCur,
const char *zWord,
fuzzer_cost rBaseCost
){
fuzzer_stem *pNew;
fuzzer_rule *pRule;
unsigned int h;
pNew = sqlite3_malloc64( sizeof(*pNew) + strlen(zWord) + 1 );
if( pNew==0 ) return 0;
memset(pNew, 0, sizeof(*pNew));
pNew->zBasis = (char*)&pNew[1];
pNew->nBasis = (fuzzer_len)strlen(zWord);
memcpy(pNew->zBasis, zWord, pNew->nBasis+1);
pRule = pCur->pVtab->pRule;
while( fuzzerSkipRule(pRule, pNew, pCur->iRuleset) ){
pRule = pRule->pNext;
}
pNew->pRule = pRule;
pNew->n = -1;
pNew->rBaseCost = pNew->rCostX = rBaseCost;
h = fuzzerHash(pNew->zBasis);
pNew->pHash = pCur->apHash[h];
pCur->apHash[h] = pNew;
pCur->nStem++;
return pNew;
}
/*
** Advance a cursor to its next row of output
*/
static int fuzzerNext(sqlite3_vtab_cursor *cur){
fuzzer_cursor *pCur = (fuzzer_cursor*)cur;
int rc;
fuzzer_stem *pStem, *pNew;
pCur->iRowid++;
/* Use the element the cursor is currently point to to create
** a new stem and insert the new stem into the priority queue.
*/
pStem = pCur->pStem;
if( pStem->rCostX>0 ){
rc = fuzzerRender(pStem, &pCur->zBuf, &pCur->nBuf);
if( rc==SQLITE_NOMEM ) return SQLITE_NOMEM;
pNew = fuzzerNewStem(pCur, pCur->zBuf, pStem->rCostX);
if( pNew ){
if( fuzzerAdvance(pCur, pNew)==0 ){
pNew->pNext = pCur->pDone;
pCur->pDone = pNew;
}else{
if( fuzzerInsert(pCur, pNew)==pNew ){
return SQLITE_OK;
}
}
}else{
return SQLITE_NOMEM;
}
}
/* Adjust the priority queue so that the first element of the
** stem list is the next lowest cost word.
*/
while( (pStem = pCur->pStem)!=0 ){
int res = fuzzerAdvance(pCur, pStem);
if( res<0 ){
return SQLITE_NOMEM;
}else if( res>0 ){
pCur->pStem = 0;
pStem = fuzzerInsert(pCur, pStem);
if( (rc = fuzzerSeen(pCur, pStem))!=0 ){
if( rc<0 ) return SQLITE_NOMEM;
continue;
}
return SQLITE_OK; /* New word found */
}
pCur->pStem = 0;
pStem->pNext = pCur->pDone;
pCur->pDone = pStem;
if( fuzzerLowestCostStem(pCur) ){
rc = fuzzerSeen(pCur, pCur->pStem);
if( rc<0 ) return SQLITE_NOMEM;
if( rc==0 ){
return SQLITE_OK;
}
}
}
/* Reach this point only if queue has been exhausted and there is
** nothing left to be output. */
pCur->rLimit = (fuzzer_cost)0;
return SQLITE_OK;
}
/*
** Called to "rewind" a cursor back to the beginning so that
** it starts its output over again. Always called at least once
** prior to any fuzzerColumn, fuzzerRowid, or fuzzerEof call.
*/
static int fuzzerFilter(
sqlite3_vtab_cursor *pVtabCursor,
int idxNum, const char *idxStr,
int argc, sqlite3_value **argv
){
fuzzer_cursor *pCur = (fuzzer_cursor *)pVtabCursor;
const char *zWord = "";
fuzzer_stem *pStem;
int idx;
fuzzerClearCursor(pCur, 1);
pCur->rLimit = 2147483647;
idx = 0;
if( idxNum & 1 ){
zWord = (const char*)sqlite3_value_text(argv[0]);
idx++;
}
if( idxNum & 2 ){
pCur->rLimit = (fuzzer_cost)sqlite3_value_int(argv[idx]);
idx++;
}
if( idxNum & 4 ){
pCur->iRuleset = (fuzzer_cost)sqlite3_value_int(argv[idx]);
idx++;
}
pCur->nullRule.pNext = pCur->pVtab->pRule;
pCur->nullRule.rCost = 0;
pCur->nullRule.nFrom = 0;
pCur->nullRule.nTo = 0;
pCur->nullRule.zFrom = "";
pCur->iRowid = 1;
assert( pCur->pStem==0 );
/* If the query term is longer than FUZZER_MX_OUTPUT_LENGTH bytes, this
** query will return zero rows. */
if( (int)strlen(zWord)<FUZZER_MX_OUTPUT_LENGTH ){
pCur->pStem = pStem = fuzzerNewStem(pCur, zWord, (fuzzer_cost)0);
if( pStem==0 ) return SQLITE_NOMEM;
pStem->pRule = &pCur->nullRule;
pStem->n = pStem->nBasis;
}else{
pCur->rLimit = 0;
}
return SQLITE_OK;
}
/*
** Only the word and distance columns have values. All other columns
** return NULL
*/
static int fuzzerColumn(sqlite3_vtab_cursor *cur, sqlite3_context *ctx, int i){
fuzzer_cursor *pCur = (fuzzer_cursor*)cur;
if( i==0 ){
/* the "word" column */
if( fuzzerRender(pCur->pStem, &pCur->zBuf, &pCur->nBuf)==SQLITE_NOMEM ){
return SQLITE_NOMEM;
}
sqlite3_result_text(ctx, pCur->zBuf, -1, SQLITE_TRANSIENT);
}else if( i==1 ){
/* the "distance" column */
sqlite3_result_int(ctx, pCur->pStem->rCostX);
}else{
/* All other columns are NULL */
sqlite3_result_null(ctx);
}
return SQLITE_OK;
}
/*
** The rowid.
*/
static int fuzzerRowid(sqlite3_vtab_cursor *cur, sqlite_int64 *pRowid){
fuzzer_cursor *pCur = (fuzzer_cursor*)cur;
*pRowid = pCur->iRowid;
return SQLITE_OK;
}
/*
** When the fuzzer_cursor.rLimit value is 0 or less, that is a signal
** that the cursor has nothing more to output.
*/
static int fuzzerEof(sqlite3_vtab_cursor *cur){
fuzzer_cursor *pCur = (fuzzer_cursor*)cur;
return pCur->rLimit<=(fuzzer_cost)0;
}
/*
** Search for terms of these forms:
**
** (A) word MATCH $str
** (B1) distance < $value
** (B2) distance <= $value
** (C) ruleid == $ruleid
**
** The distance< and distance<= are both treated as distance<=.
** The query plan number is a bit vector:
**
** bit 1: Term of the form (A) found
** bit 2: Term like (B1) or (B2) found
** bit 3: Term like (C) found
**
** If bit-1 is set, $str is always in filter.argv[0]. If bit-2 is set
** then $value is in filter.argv[0] if bit-1 is clear and is in
** filter.argv[1] if bit-1 is set. If bit-3 is set, then $ruleid is
** in filter.argv[0] if bit-1 and bit-2 are both zero, is in
** filter.argv[1] if exactly one of bit-1 and bit-2 are set, and is in
** filter.argv[2] if both bit-1 and bit-2 are set.
*/
static int fuzzerBestIndex(sqlite3_vtab *tab, sqlite3_index_info *pIdxInfo){
int iPlan = 0;
int iDistTerm = -1;
int iRulesetTerm = -1;
int i;
int seenMatch = 0;
const struct sqlite3_index_constraint *pConstraint;
double rCost = 1e12;
pConstraint = pIdxInfo->aConstraint;
for(i=0; i<pIdxInfo->nConstraint; i++, pConstraint++){
if( pConstraint->iColumn==0
&& pConstraint->op==SQLITE_INDEX_CONSTRAINT_MATCH ){
seenMatch = 1;
}
if( pConstraint->usable==0 ) continue;
if( (iPlan & 1)==0
&& pConstraint->iColumn==0
&& pConstraint->op==SQLITE_INDEX_CONSTRAINT_MATCH
){
iPlan |= 1;
pIdxInfo->aConstraintUsage[i].argvIndex = 1;
pIdxInfo->aConstraintUsage[i].omit = 1;
rCost /= 1e6;
}
if( (iPlan & 2)==0
&& pConstraint->iColumn==1
&& (pConstraint->op==SQLITE_INDEX_CONSTRAINT_LT
|| pConstraint->op==SQLITE_INDEX_CONSTRAINT_LE)
){
iPlan |= 2;
iDistTerm = i;
rCost /= 10.0;
}
if( (iPlan & 4)==0
&& pConstraint->iColumn==2
&& pConstraint->op==SQLITE_INDEX_CONSTRAINT_EQ
){
iPlan |= 4;
pIdxInfo->aConstraintUsage[i].omit = 1;
iRulesetTerm = i;
rCost /= 10.0;
}
}
if( iPlan & 2 ){
pIdxInfo->aConstraintUsage[iDistTerm].argvIndex = 1+((iPlan&1)!=0);
}
if( iPlan & 4 ){
int idx = 1;
if( iPlan & 1 ) idx++;
if( iPlan & 2 ) idx++;
pIdxInfo->aConstraintUsage[iRulesetTerm].argvIndex = idx;
}
pIdxInfo->idxNum = iPlan;
if( pIdxInfo->nOrderBy==1
&& pIdxInfo->aOrderBy[0].iColumn==1
&& pIdxInfo->aOrderBy[0].desc==0
){
pIdxInfo->orderByConsumed = 1;
}
if( seenMatch && (iPlan&1)==0 ) rCost = 1e99;
pIdxInfo->estimatedCost = rCost;
return SQLITE_OK;
}
/*
** A virtual table module that implements the "fuzzer".
*/
static sqlite3_module fuzzerModule = {
0, /* iVersion */
fuzzerConnect,
fuzzerConnect,
fuzzerBestIndex,
fuzzerDisconnect,
fuzzerDisconnect,
fuzzerOpen, /* xOpen - open a cursor */
fuzzerClose, /* xClose - close a cursor */
fuzzerFilter, /* xFilter - configure scan constraints */
fuzzerNext, /* xNext - advance a cursor */
fuzzerEof, /* xEof - check for end of scan */
fuzzerColumn, /* xColumn - read data */
fuzzerRowid, /* xRowid - read data */
0, /* xUpdate */
0, /* xBegin */
0, /* xSync */
0, /* xCommit */
0, /* xRollback */
0, /* xFindMethod */
0, /* xRename */
};
#endif /* SQLITE_OMIT_VIRTUALTABLE */
#ifdef _WIN32
__declspec(dllexport)
#endif
int sqlite3_fuzzer_init(
sqlite3 *db,
char **pzErrMsg,
const sqlite3_api_routines *pApi
){
int rc = SQLITE_OK;
SQLITE_EXTENSION_INIT2(pApi);
#ifndef SQLITE_OMIT_VIRTUALTABLE
rc = sqlite3_create_module(db, "fuzzer", &fuzzerModule, 0);
#endif
return rc;
}