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Overview
Comment: | Change the way the fuzzer (test_fuzzer.c) works so that it loads its configuration from a database table. |
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Downloads: | Tarball | ZIP archive |
Timelines: | family | ancestors | descendants | both | trunk |
Files: | files | file ages | folders |
SHA1: |
90b7b957f8933047fd2878048dfa3ec4 |
User & Date: | dan 2012-02-20 20:03:48.835 |
Context
2012-02-20
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22:44 | Updates to the instructions in the header comment of the fuzzer implementation. New test cases for the fuzzer. (check-in: bf1dc7907c user: drh tags: trunk) | |
20:03 | Change the way the fuzzer (test_fuzzer.c) works so that it loads its configuration from a database table. (check-in: 90b7b957f8 user: dan tags: trunk) | |
19:36 | Fix a case in test_fuzzer.c causing transformations from the wrong ruleset to be applied in some cases. (check-in: cb5f5ebc56 user: dan tags: trunk) | |
Changes
Changes to src/test_fuzzer.c.
1 2 3 4 5 6 7 8 9 10 11 12 | /* ** 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. ** ************************************************************************* ** | | | | | | | > > > > > | | > | > > > | > | > > > > | | | < < < | < < < < < | | > > > | > > > > | | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | /* ** 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 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 ** that the cost of 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. ** ** 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. |
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92 93 94 95 96 97 98 | ** 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 ** | > > | | < | | < < < < | | | > | 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 | ** 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. */ #include "sqlite3.h" #include <stdlib.h> #include <string.h> #include <assert.h> #include <stdio.h> |
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195 196 197 198 199 200 201 | /* ** 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 */ | < | 206 207 208 209 210 211 212 213 214 215 216 217 218 219 | /* ** 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 */ |
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220 221 222 223 224 225 226 | 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 */ }; | < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < | 230 231 232 233 234 235 236 237 238 239 240 241 242 243 | 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; |
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294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 | pTail->pNext = pB; }else{ pTail->pNext = pA; } return head.pNext; } /* ** 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; | > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > < < < < < < < < < < < < < < < < < < < | 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 | 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 */ ){ int iRuleset = sqlite3_column_int(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 = strlen(zFrom); nTo = 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("cost must be between 1 and %d", FUZZER_MX_COST); rc = SQLITE_ERROR; }else if( nFrom>FUZZER_MX_LENGTH || nTo>FUZZER_MX_LENGTH ){ *pzErr = sqlite3_mprintf("maximum string length is %d", FUZZER_MX_LENGTH); rc = SQLITE_ERROR; }else if( iRuleset<0 || iRuleset>FUZZER_MX_RULEID ){ *pzErr = sqlite3_mprintf( "ruleset must be between 0 and %d", FUZZER_MX_RULEID); rc = SQLITE_ERROR; }else{ pRule = sqlite3_malloc( sizeof(*pRule) + nFrom + nTo ); if( pRule==0 ){ rc = SQLITE_NOMEM; }else{ memset(pRule, 0, sizeof(*pRule)); pRule->zFrom = &pRule->zTo[nTo+1]; pRule->nFrom = nFrom; memcpy(pRule->zFrom, zFrom, nFrom+1); memcpy(pRule->zTo, zTo, nTo+1); pRule->nTo = nTo; pRule->rCost = nCost; pRule->iRuleset = 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; } /* ** 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{ int nModule; /* Length of zModule, in bytes */ nModule = strlen(zModule); pNew = sqlite3_malloc( sizeof(*pNew) + nModule + 1); if( pNew==0 ){ rc = SQLITE_NOMEM; }else{ memset(pNew, 0, sizeof(*pNew)); pNew->zClassName = (char*)&pNew[1]; memcpy(pNew->zClassName, zModule, nModule+1); rc = fuzzerLoadRules(db, pNew, zDb, argv[3], pzErr); if( rc==SQLITE_OK ){ sqlite3_declare_vtab(db, "CREATE TABLE x(word, distance,ruleset)"); }else{ sqlite3_free(pNew); pNew = 0; } } } *ppVtab = (sqlite3_vtab *)pNew; return rc; } /* Note that for this virtual table, the xCreate and xConnect ** methods are identical. */ 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; } /* The xDisconnect and xDestroy methods are also the same */ /* ** 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. */ |
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475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 | /* ** 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; | > | | 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 | /* ** 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; const int iSet = pCur->iRuleset; 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( pRule && pRule->iRuleset!=iSet ); pStem->pRule = pRule; if( pRule && fuzzerCost(pStem)>pCur->rLimit ) pStem->pRule = 0; } return 0; } /* |
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860 861 862 863 864 865 866 | pIdxInfo->orderByConsumed = 1; } pIdxInfo->estimatedCost = (double)10000; return SQLITE_OK; } | < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < | | 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 | pIdxInfo->orderByConsumed = 1; } pIdxInfo->estimatedCost = (double)10000; return SQLITE_OK; } /* ** A virtual table module that provides read-only access to a ** Tcl global variable namespace. */ 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 */ }; |
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Changes to test/fuzzer1.test.
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19 20 21 22 23 24 25 | ifcapable !vtab { finish_test return } register_fuzzer_module db | > > > > > | | > | | > > > > > > > > > > > > > > > | > | | > > > > | > > > > > > > > > | | | | > | < > > > > | < | < | | | | > > > | < | > > > > | | | < | > > > > | | | < | > > > | | | 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 | ifcapable !vtab { finish_test return } register_fuzzer_module db # Check configuration errors. # do_catchsql_test fuzzer1-1.1 { CREATE VIRTUAL TABLE f USING fuzzer; } {1 {fuzzer: wrong number of CREATE VIRTUAL TABLE arguments}} do_catchsql_test fuzzer1-1.2 { CREATE VIRTUAL TABLE f USING fuzzer(one, two); } {1 {fuzzer: wrong number of CREATE VIRTUAL TABLE arguments}} do_catchsql_test fuzzer1-1.3 { CREATE VIRTUAL TABLE f USING fuzzer(nosuchtable); } {1 {fuzzer: no such table: main.nosuchtable}} do_catchsql_test fuzzer1-1.4 { CREATE TEMP TABLE nosuchtable(a, b, c, d); CREATE VIRTUAL TABLE f USING fuzzer(nosuchtable); } {1 {fuzzer: no such table: main.nosuchtable}} do_catchsql_test fuzzer1-1.5 { DROP TABLE temp.nosuchtable; CREATE TABLE nosuchtable(a, b, c, d); CREATE VIRTUAL TABLE temp.f USING fuzzer(nosuchtable); } {1 {fuzzer: no such table: temp.nosuchtable}} do_catchsql_test fuzzer1-1.6 { DROP TABLE IF EXISTS f_rules; CREATE TABLE f_rules(a, b, c); CREATE VIRTUAL TABLE f USING fuzzer(f_rules); } {1 {fuzzer: f_rules has 3 columns, expected 4}} do_catchsql_test fuzzer1-1.7 { DROP TABLE IF EXISTS f_rules; CREATE TABLE f_rules(a, b, c, d, e); CREATE VIRTUAL TABLE f USING fuzzer(f_rules); } {1 {fuzzer: f_rules has 5 columns, expected 4}} do_execsql_test fuzzer1-2.1 { CREATE TABLE f1_rules(ruleset DEFAULT 0, cfrom, cto, cost); INSERT INTO f1_rules(cfrom, cto, cost) VALUES('e','a',1); INSERT INTO f1_rules(cfrom, cto, cost) VALUES('a','e',10); INSERT INTO f1_rules(cfrom, cto, cost) VALUES('e','o',100); CREATE VIRTUAL TABLE f1 USING fuzzer(f1_rules); } {} do_execsql_test fuzzer1-2.1 { SELECT word, distance FROM f1 WHERE word MATCH 'abcde' } { abcde 0 abcda 1 ebcde 10 ebcda 11 abcdo 100 ebcdo 110 obcde 110 obcda 111 obcdo 210 } do_execsql_test fuzzer1-2.4 { INSERT INTO f1_rules(ruleset, cfrom, cto, cost) VALUES(1,'b','x',1); INSERT INTO f1_rules(ruleset, cfrom, cto, cost) VALUES(1,'d','y',10); INSERT INTO f1_rules(ruleset, cfrom, cto, cost) VALUES(1,'y','z',100); DROP TABLE f1; CREATE VIRTUAL TABLE f1 USING fuzzer(f1_rules); } {} do_execsql_test fuzzer1-2.5 { SELECT word, distance FROM f1 WHERE word MATCH 'abcde' } { abcde 0 abcda 1 ebcde 10 ebcda 11 abcdo 100 ebcdo 110 obcde 110 obcda 111 obcdo 210 } do_execsql_test fuzzer1-2.6 { SELECT word, distance FROM f1 WHERE word MATCH 'abcde' AND ruleset=0 } { abcde 0 abcda 1 ebcde 10 ebcda 11 abcdo 100 ebcdo 110 obcde 110 obcda 111 obcdo 210 } do_execsql_test fuzzer1-2.7 { SELECT word, distance FROM f1 WHERE word MATCH 'abcde' AND ruleset=1 } { abcde 0 axcde 1 abcye 10 axcye 11 abcze 110 axcze 111 } do_test fuzzer1-1.8 { db eval { SELECT word, distance FROM f1 WHERE word MATCH 'abcde' AND distance<100 } } {abcde 0 abcda 1 ebcde 10 ebcda 11} do_test fuzzer1-1.9 { db eval { |
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98 99 100 101 102 103 104 | SELECT word, distance FROM f1 WHERE word MATCH 'abcde' AND distance<=11 AND ruleset=1 } } {abcde 0 axcde 1 abcye 10 axcye 11} do_test fuzzer1-2.0 { execsql { | < > | | | | | | | | | | | | | | | | < | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | > > | 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 | SELECT word, distance FROM f1 WHERE word MATCH 'abcde' AND distance<=11 AND ruleset=1 } } {abcde 0 axcde 1 abcye 10 axcye 11} do_test fuzzer1-2.0 { execsql { -- costs based on English letter frequencies CREATE TEMP TABLE f2_rules(ruleset, cFrom, cTo, cost); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('a','e',24); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('a','o',47); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('a','u',50); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('e','a',23); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('e','i',33); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('e','o',37); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('i','e',33); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('i','y',33); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('o','a',41); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('o','e',46); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('o','u',57); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('u','o',58); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('y','i',33); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('t','th',70); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('th','t',66); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('a','',84); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','b',106); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('b','',106); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','c',94); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('c','',94); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','d',89); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('d','',89); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','e',83); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('e','',83); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','f',97); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('f','',97); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','g',99); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('g','',99); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','h',86); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('h','',86); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','i',85); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('i','',85); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','j',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('j','',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','k',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('k','',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','l',89); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('l','',89); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','m',96); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('m','',96); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','n',85); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('n','',85); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','o',85); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('o','',85); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','p',100); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('p','',100); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','q',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('q','',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','r',86); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('r','',86); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','s',86); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('s','',86); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','t',84); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('t','',84); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','u',94); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('u','',94); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','v',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('v','',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','w',96); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('w','',96); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','x',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('x','',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','y',100); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('y','',100); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('','z',120); INSERT INTO f2_rules(cFrom,cTo,cost) VALUES('z','',120); CREATE VIRTUAL TABLE temp.f2 USING fuzzer(f2_rules); -- Street names for the 28269 ZIPCODE. -- CREATE TEMP TABLE streetname(n TEXT UNIQUE); INSERT INTO streetname VALUES('abbotsinch'); INSERT INTO streetname VALUES('abbottsgate'); INSERT INTO streetname VALUES('abbywood'); |
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1431 1432 1433 1434 1435 1436 1437 | SELECT DISTINCT streetname.n FROM f2, streetname WHERE f2.word MATCH 'tayle' AND f2.distance<=200 AND streetname.n>=f2.word AND streetname.n<=(f2.word || x'F7BFBFBF') } } {{tyler finley} trailer taymouth steelewood tallia tallu talwyn thelema} | | | | | | | > | 1480 1481 1482 1483 1484 1485 1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497 | SELECT DISTINCT streetname.n FROM f2, streetname WHERE f2.word MATCH 'tayle' AND f2.distance<=200 AND streetname.n>=f2.word AND streetname.n<=(f2.word || x'F7BFBFBF') } } {{tyler finley} trailer taymouth steelewood tallia tallu talwyn thelema} forcedelete test.db2 do_execsql_test fuzzer1-4.1 { ATTACH 'test.db2' AS aux; CREATE TABLE aux.f3_rules(ruleset, cfrom, cto, cost); INSERT INTO f3_rules(ruleset, cfrom, cto, cost) VALUES(0, 'x','y', 10); INSERT INTO f3_rules(ruleset, cfrom, cto, cost) VALUES(1, 'a','b', 10); CREATE VIRTUAL TABLE aux.f3 USING fuzzer(f3_rules); SELECT word FROM f3 WHERE word MATCH 'ax' } {ax ay} finish_test |