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Long presentation for "Testing Database Engines...

Manuel Rigger
November 03, 2020
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Long presentation for "Testing Database Engines via Pivoted Query Synthesis" at OSDI '20

Manuel Rigger

November 03, 2020
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  1. Testing Database Engines via Pivoted Query Synthesis Manuel Rigger Zhendong

    Su ETH Zurich, Switzerland 11/05/2020 @RiggerManuel @ast_eth https://people.inf.ethz.ch/suz/
  2. 3 Database Management Systems (DBMSs) PostgreSQL “it is seems likely

    that there are over one trillion (1e12) SQLite databases in active use” https://www.sqlite.org/mostdeployed.html
  3. 4 Database Management Systems (DBMSs) PostgreSQL We found 96 unique

    bugs in these DBMSs, 78 of which were fixed!
  4. 6 Example: SQLite3 Bug c0 0 1 2 NULL t0

    CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; https://sqlite.org/src/tktview/80256748471a01
  5. 7 Example: SQLite3 Bug c0 0 1 2 NULL t0

    CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; IS NOT is a “null-safe” comparison operator https://sqlite.org/src/tktview/80256748471a01
  6. 8 Example: SQLite3 Bug c0 0 1 2 NULL t0

    CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; https://sqlite.org/src/tktview/80256748471a01
  7. 9 Example: SQLite3 Bug c0 0 1 2 NULL t0

    0 CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; TRUE https://sqlite.org/src/tktview/80256748471a01
  8. 10 Example: SQLite3 Bug c0 0 1 2 NULL t0

    0 CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; TRUE 0 https://sqlite.org/src/tktview/80256748471a01
  9. 11 Example: SQLite3 Bug c0 0 1 2 NULL t0

    1 CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; 0 FALSE https://sqlite.org/src/tktview/80256748471a01
  10. 12 Example: SQLite3 Bug c0 0 1 2 NULL t0

    0 2 2 CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; TRUE https://sqlite.org/src/tktview/80256748471a01
  11. 13 Example: SQLite3 Bug c0 0 1 2 NULL t0

    0 2 NULL NULL CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; TRUE https://sqlite.org/src/tktview/80256748471a01
  12. 14 Example: SQLite3 Bug c0 0 1 2 NULL t0

    NULL CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; TRUE 0 2 NULL https://sqlite.org/src/tktview/80256748471a01
  13. 15 Example: SQLite3 Bug c0 0 1 2 NULL t0

    NULL CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; TRUE 0 2 NULL 0 2 https://sqlite.org/src/tktview/80256748471a01
  14. 16 Example: SQLite3 Bug c0 0 1 2 NULL t0

    NULL CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; TRUE  NULL was not contained in the result set! 0 2 NULL 0 2 https://sqlite.org/src/tktview/80256748471a01
  15. 17 Background: Differential Testing PostgreSQL SELECT c0 FROM t0 WHERE

    t0.c0 IS NOT 1; Massive Stochastic Testing of SQL by Slutz, 1998.
  16. 18 Background: Differential Testing PostgreSQL RS1 RS2 RS3 SELECT c0

    FROM t0 WHERE t0.c0 IS NOT 1; Massive Stochastic Testing of SQL by Slutz, 1998.
  17. 19 Background: Differential Testing PostgreSQL RS1 RS2 RS3 SELECT c0

    FROM t0 WHERE t0.c0 IS NOT 1; Check that all DBMSs compute the same result (RS1 = RS2 = RS3 ) Massive Stochastic Testing of SQL by Slutz, 1998.
  18. 23 Background: Differential Testing CREATE TABLE t0(c0); CREATE INDEX i0

    ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (3), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1;
  19. 24 Background: Differential Testing CREATE TABLE t0(c0); CREATE INDEX i0

    ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (3), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; MySQL and PostgreSQL require a data type definition
  20. 25 Background: Differential Testing CREATE TABLE t0(c0); CREATE INDEX i0

    ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (3), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; PostgreSQL provides an IS DISTINCT FROM operator, and MySQL a <=> null-safe comparison operator
  21. 27 PQS Idea c0 0 1 2 NULL t0 CREATE

    TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (3), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; Validate the result set based on one randomly-selected row
  22. 28 PQS Idea c0 0 1 2 NULL t0 CREATE

    TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (3), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; Pivot row Validate the result set based on one randomly-selected row
  23. 29 PQS Idea c0 0 1 2 NULL t0 CREATE

    TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (3), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1; Generate a query that is guaranteed to at least fetch the pivot row NULL TRUE
  24. 30 PQS Idea c0 0 1 2 NULL t0 CREATE

    TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (3), (NULL); SELECT c0 FROM t0 WHERE t0.c0 IS NOT 1;  If the pivot row is missing from the result set a bug has been detected 0 2
  25. 31 Approach Randomly generate database Select pivot row Generate query

    for the pivot row Validate that the pivot row is contained
  26. 32 Approach Randomly generate database Select pivot row Generate query

    for the pivot row Validate that the pivot row is contained CREATE TABLE t0(c0); CREATE INDEX i0 ON t0(1) WHERE c0 NOT NULL; INSERT INTO t0 (c0) VALUES (0), (1), (2), (3), (NULL); Statements are heuristically generated based on the DBMS’ SQL dialect
  27. 33 Approach Randomly generate database Select pivot row Generate query

    for the pivot row Validate that the pivot row is contained One random row from multiple tables and views
  28. 34 Approach Randomly generate database Select pivot row Generate query

    for the pivot row Validate that the pivot row is contained Generate predicatesthat evaluate to TRUE for the pivot row and use them in JOIN and WHERE clauses SELECT c0 FROM t0 WHERE
  29. 35 Random Expression Generation t0.c0 IS NOT 1; Randomly generate

    database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1
  30. 36 Random Expression Generation t0.c0 IS NOT 1; We implemented

    an expression evaluator for each node Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1
  31. 37 Random Expression Generation c0 0 1 2 NULL t0

    Evaluate the tree based on the pivot row Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1
  32. 38 Random Expression Generation Column references return the values from

    the pivot row c0 0 1 2 NULL t0 Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1
  33. 39 Random Expression Generation Column references return the values from

    the pivot row c0 0 1 2 NULL t0 Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1 NULL
  34. 40 Random Expression Generation Constant nodes return their assigned literal

    values c0 0 1 2 NULL t0 Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1 NULL
  35. 41 Random Expression Generation Constant nodes return their assigned literal

    values c0 0 1 2 NULL t0 Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1 NULL 1
  36. 42 Random Expression Generation Compound nodes compute their result based

    on their children TRUE c0 0 1 2 NULL t0 Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1 NULL 1
  37. 43 Random Expression Generation Compound nodes compute their result based

    on their children TRUE c0 0 1 2 NULL t0 Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained IS NOT t0.c0 1 NULL 1 TRUE
  38. 44 t0.c0 IS NOT 1; Query Synthesis SELECT c0 c0

    FROM t0 WHERE Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained
  39. 45 t0.c0 IS NOT 1; Query Synthesis SELECT c0 c0

    FROM t0 WHERE What if the expression does not evaluate to TRUE? Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained
  40. 46 Random Expression Rectification switch (result) { case TRUE: result

    = randexpr; case FALSE: result = NOT randexpr; case NULL: result = randexpr IS NULL; } Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained
  41. 47 Random Expression Rectification switch (result) { case TRUE: result

    = randexpr; case FALSE: result = NOT randexpr; case NULL: result = randexpr IS NULL; } Alternatively, we could validate that the pivot row is expectedly not fetched Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained
  42. 48 Random Expression Rectification Randomly generate database Select pivot row

    Generate query for the pivot row Validate that the pivot row is contained • DISTINCT clauses • ORDER BY clauses • DBMS-specific clauses (e.g., FOR UPDATE)
  43. 49 Approach SELECT (NULL) INTERSECT SELECT c0 FROM t0 WHERE

    NULL IS NOT 1; Rely on the DBMS to check whether the row is contained Randomly generate database Select pivot row Generate query for the pivot row Validate that the pivot row is contained
  44. 50 Approach Randomly generate database Select pivot row Generate query

    for the pivot row Validate that the pivot row is contained
  45. 51 Approach Randomly generate database Select pivot row Generate query

    for the pivot row Validate that the pivot row is contained
  46. 52 Approach Randomly generate database Select pivot row Generate query

    for the pivot row Validate that the pivot row is contained We generate 100,000 queries for each generated database
  47. 55 Bugs Overview DBMS Fixed Verified SQLite 64 0 MySQL

    17 7 PostgreSQL 5 3 96 bugs were unique, previously unknown ones
  48. 56 Bugs Overview The SQLite developers quickly responded to all

    our bug reports → we focused on this DBMS DBMS Fixed Verified SQLite 64 0 MySQL 17 7 PostgreSQL 5 3
  49. 57 Oracles DBMS Logic Error Crash SQLite 46 17 2

    MySQL 14 10 1 PostgreSQL 1 7 1 61 were logic bugs
  50. 58 Example: SQLite CREATE TABLE t1(c1, c2, c3, c4, PRIMARY

    KEY (c4, c3)); INSERT INTO t1(c3) VALUES (0), (0), (0), (0), (0), (0), (0), (0), (0), (0), (NULL), (1), (0); UPDATE t1 SET c2 = 0; INSERT INTO t1(c1) VALUES (0), (0), (NULL), (0), (0); ANALYZE t1; UPDATE t1 SET c3 = 1; SELECT DISTINCT * FROM t1 WHERE t1.c3 = 1; https://www.sqlite.org/src/tktview?name=ced41c7c7d
  51. 59 Example: SQLite CREATE TABLE t1(c1, c2, c3, c4, PRIMARY

    KEY (c4, c3)); INSERT INTO t1(c3) VALUES (0), (0), (0), (0), (0), (0), (0), (0), (0), (0), (NULL), (1), (0); UPDATE t1 SET c2 = 0; INSERT INTO t1(c1) VALUES (0), (0), (NULL), (0), (0); ANALYZE t1; UPDATE t1 SET c3 = 1; SELECT DISTINCT * FROM t1 WHERE t1.c3 = 1; ANALYZE gathers statistics about tables, which are then used for query planning https://www.sqlite.org/src/tktview?name=ced41c7c7d
  52. 60 Example: SQLite CREATE TABLE t1(c1, c2, c3, c4, PRIMARY

    KEY (c4, c3)); INSERT INTO t1(c3) VALUES (0), (0), (0), (0), (0), (0), (0), (0), (0), (0), (NULL), (1), (0); UPDATE t1 SET c2 = 0; INSERT INTO t1(c1) VALUES (0), (0), (NULL), (0), (0); ANALYZE t1; UPDATE t1 SET c3 = 1; SELECT DISTINCT * FROM t1 WHERE t1.c3 = 1; NULL 0 1 NULL  https://www.sqlite.org/src/tktview?name=ced41c7c7d
  53. 61 Example: SQLite CREATE TABLE t1(c1, c2, c3, c4, PRIMARY

    KEY (c4, c3)); INSERT INTO t1(c3) VALUES (0), (0), (0), (0), (0), (0), (0), (0), (0), (0), (NULL), (1), (0); UPDATE t1 SET c2 = 0; INSERT INTO t1(c1) VALUES (0), (0), (NULL), (0), (0); ANALYZE t1; UPDATE t1 SET c3 = 1; SELECT DISTINCT * FROM t1 WHERE t1.c3 = 1; NULL 0 1 NULL  A bug in the skip-scan optimization caused this logic bug https://www.sqlite.org/src/tktview?name=ced41c7c7d
  54. 62 Example: SQLite CREATE TABLE t1(c1, c2, c3, c4, PRIMARY

    KEY (c4, c3)); INSERT INTO t1(c3) VALUES (0), (0), (0), (0), (0), (0), (0), (0), (0), (0), (NULL), (1), (0); UPDATE t1 SET c2 = 0; INSERT INTO t1(c1) VALUES (0), (0), (NULL), (0), (0); ANALYZE t1; UPDATE t1 SET c3 = 1; SELECT DISTINCT * FROM t1 WHERE t1.c3 = 1; NULL 0 1 NULL 0 NULL 1 NULL NULL NULL 1 NULL https://www.sqlite.org/src/tktview?name=ced41c7c7d ✓
  55. 63 Example: SQLite CREATE TABLE t1(c1, c2, c3, c4, PRIMARY

    KEY (c4, c3)); INSERT INTO t1(c3) VALUES (0), (0), (0), (0), (0), (0), (0), (0), (0), (0), (NULL), (1), (0); UPDATE t1 SET c2 = 0; INSERT INTO t1(c1) VALUES (0), (0), (NULL), (0), (0); ANALYZE t1; UPDATE t1 SET c3 = 1; SELECT DISTINCT * FROM t1 WHERE t1.c3 = 1; NULL 0 1 NULL 0 NULL 1 NULL NULL NULL 1 NULL https://www.sqlite.org/src/tktview?name=ced41c7c7d ✓ The bug was classified as “Severe” and quickly fixed
  56. 64 Result: Bug in PostgreSQL CREATE TABLE t0(c0 INT PRIMARY

    KEY, c1 INT); CREATE TABLE t1(c0 INT) INHERITS (t0); INSERT INTO t0(c0, c1) VALUES(0, 0); c0 c1 0 0 c0 c1 t0 t1 https://www.postgresql.org/message-id/CA%2Bu7OA7VLKf_vEr6kLF3MnWSA9LToJYncgpNX2tQ-oWzYCBQAw%40mail.gmail.com
  57. 65 Result: Bug in PostgreSQL CREATE TABLE t0(c0 INT PRIMARY

    KEY, c1 INT); CREATE TABLE t1(c0 INT) INHERITS (t0); INSERT INTO t0(c0, c1) VALUES(0, 0); INSERT INTO t1(c0, c1) VALUES(0, 1); c0 c1 0 0 0 1 c0 c1 0 1 t0 t1 https://www.postgresql.org/message-id/CA%2Bu7OA7VLKf_vEr6kLF3MnWSA9LToJYncgpNX2tQ-oWzYCBQAw%40mail.gmail.com
  58. 66 Result: Bug in PostgreSQL CREATE TABLE t0(c0 INT PRIMARY

    KEY, c1 INT); CREATE TABLE t1(c0 INT) INHERITS (t0); INSERT INTO t0(c0, c1) VALUES(0, 0); INSERT INTO t1(c0, c1) VALUES(0, 1); c0 c1 0 0 0 1 c0 c1 0 1 t0 t1 The inheritance relationship causes the row to be inserted both in t0 and t1 https://www.postgresql.org/message-id/CA%2Bu7OA7VLKf_vEr6kLF3MnWSA9LToJYncgpNX2tQ-oWzYCBQAw%40mail.gmail.com
  59. 67 Result: Bug in PostgreSQL CREATE TABLE t0(c0 INT PRIMARY

    KEY, c1 INT); CREATE TABLE t1(c0 INT) INHERITS (t0); INSERT INTO t0(c0, c1) VALUES(0, 0); INSERT INTO t1(c0, c1) VALUES(0, 1); c0 c1 0 0 0 1 c0 c1 0 1 t0 t1 SELECT c0, c1 FROM t0 GROUP BY c0, c1; 0 0  https://www.postgresql.org/message-id/CA%2Bu7OA7VLKf_vEr6kLF3MnWSA9LToJYncgpNX2tQ-oWzYCBQAw%40mail.gmail.com
  60. 68 Result: Bug in PostgreSQL CREATE TABLE t0(c0 INT PRIMARY

    KEY, c1 INT); CREATE TABLE t1(c0 INT) INHERITS (t0); INSERT INTO t0(c0, c1) VALUES(0, 0); INSERT INTO t1(c0, c1) VALUES(0, 1); c0 c1 0 0 0 1 c0 c1 0 1 t0 t1 SELECT c0, c1 FROM t0 GROUP BY c0, c1; 0 0 An optimization incorrectly simplified the GROUP BY clause  https://www.postgresql.org/message-id/CA%2Bu7OA7VLKf_vEr6kLF3MnWSA9LToJYncgpNX2tQ-oWzYCBQAw%40mail.gmail.com
  61. 69 Result: Bug in PostgreSQL CREATE TABLE t0(c0 INT PRIMARY

    KEY, c1 INT); CREATE TABLE t1(c0 INT) INHERITS (t0); INSERT INTO t0(c0, c1) VALUES(0, 0); INSERT INTO t1(c0, c1) VALUES(0, 1); c0 c1 0 0 0 1 c0 c1 0 1 t0 t1 SELECT c0, c1 FROM t0 GROUP BY c0, c1; 0 0 0 1 ✓ https://www.postgresql.org/message-id/CA%2Bu7OA7VLKf_vEr6kLF3MnWSA9LToJYncgpNX2tQ-oWzYCBQAw%40mail.gmail.com
  62. 70 Result: Bug in MySQL c0 1 t0 CREATE TABLE

    t0(c0 INT); INSERT INTO t0(c0) VALUES (1); SELECT * FROM t0 WHERE 123 != (NOT (NOT 123));  {} https://bugs.mysql.com/bug.php?id=95900
  63. 71 Result: Bug in MySQL c0 1 t0 CREATE TABLE

    t0(c0 INT); INSERT INTO t0(c0) VALUES (1); SELECT * FROM t0 WHERE 123 != (NOT (NOT 123));  {} The double negation cannot be removed due to MySQL’s flexible type system https://bugs.mysql.com/bug.php?id=95900
  64. 72 Result: Bug in MySQL c0 1 t0 CREATE TABLE

    t0(c0 INT); INSERT INTO t0(c0) VALUES (1); SELECT * FROM t0 WHERE 123 != (NOT (NOT 123)); 0 ✓ https://bugs.mysql.com/bug.php?id=95900
  65. 73 Oracles DBMS Logic Error Crash SQLite 46 17 2

    MySQL 14 10 1 PostgreSQL 1 7 1 Error bugs are due to unexpected (internal) errors
  66. 74 Example: SQLite3 Bug CREATE TABLE t0(c0, c1 REAL PRIMARY

    KEY); INSERT INTO t0(c0, c1) VALUES (TRUE, 9223372036854775807), (TRUE, 0); UPDATE t0 SET c0 = NULL; UPDATE OR REPLACE t0 SET c1 = 1; SELECT DISTINCT * FROM t0 WHERE (t0.c0 IS NULL); Database disk image is malformed
  67. 75 Discussion: Implementation Effort • Literal evaluator • Simpler than

    PL AST Interpreters → No mutable state • Simpler than query engines → only a single row needs to be considered
  68. 76 Discussion: Implementation Effort • Literal evaluator • Simpler than

    PL AST Interpreters → No mutable state • Simpler than query engines → only a single row needs to be considered • Operators are implemented naively • The performance of the DBMS is the bottleneck
  69. 77 Discussion: Implementation Effort • Literal evaluator • Simpler than

    PL AST Interpreters → No mutable state • Simpler than query engines → only a single row needs to be considered • Operators are implemented naively • The performance of the DBMS is the bottleneck • Higher implementation effort for functions (e.g. printf) and complex operators
  70. 78 Discussion: Limitations • Requires understanding of the SQL semantics

    • Aggregate and window functions • Ordering • Duplicate rows
  71. 79 Discussion: Bug Importance https://www.mail-archive.com/[email protected]/msg117440.html CREATE TABLE t0 (c0); CREATE

    TABLE t1 (c1); INSERT INTO t0 VALUES (1); SELECT c0 FROM t0 LEFT JOIN t1 ON c1=c0 WHERE NOT (c1 IS NOT NULL AND c1=2);
  72. 80 Discussion: Bug Importance This is a cut-down example, right

    ? You can't possibly mean to do that WHERE clause in production code. https://www.mail-archive.com/[email protected]/msg117440.html CREATE TABLE t0 (c0); CREATE TABLE t1 (c1); INSERT INTO t0 VALUES (1); SELECT c0 FROM t0 LEFT JOIN t1 ON c1=c0 WHERE NOT (c1 IS NOT NULL AND c1=2);
  73. 81 Discussion: Bug Importance I might not spell it like

    that myself, but a code generator would do it (and much worse!). This example was simplified from a query generated by a Django ORM queryset using .exclude(nullable_joined_table__column=1), for instance. This is a cut-down example, right ? You can't possibly mean to do that WHERE clause in production code. https://www.mail-archive.com/[email protected]/msg117440.html CREATE TABLE t0 (c0); CREATE TABLE t1 (c1); INSERT INTO t0 VALUES (1); SELECT c0 FROM t0 LEFT JOIN t1 ON c1=c0 WHERE NOT (c1 IS NOT NULL AND c1=2);
  74. 82 Discussion: Bug Importance I might not spell it like

    that myself, but a code generator would do it (and much worse!). This example was simplified from a query generated by a Django ORM queryset using .exclude(nullable_joined_table__column=1), for instance. This is a cut-down example, right ? You can't possibly mean to do that WHERE clause in production code. https://www.mail-archive.com/[email protected]/msg117440.html Even “obscure” bugs might affect users CREATE TABLE t0 (c0); CREATE TABLE t1 (c1); INSERT INTO t0 VALUES (1); SELECT c0 FROM t0 LEFT JOIN t1 ON c1=c0 WHERE NOT (c1 IS NOT NULL AND c1=2);
  75. 84 Overview Pivoted Query Synthesis (PQS) Non-optimizing Reference Engine Construction

    (NoREC) Ternary Logic Query Partitioning (TLP) Detecting optimization bugs by rewriting the query so that it cannot be optimized >150 bugs
  76. 85 Overview Pivoted Query Synthesis (PQS) Non-optimizing Reference Engine Construction

    (NoREC) Ternary Logic Query Partitioning (TLP) Partition the query into several partitioning queries, which is applicable to test various features >150 bugs
  77. 87 @RiggerManuel [email protected] Summary Goal: Detect logic bugs PQS randomly

    selects a pivot row Rectify a random expression Evaluation: Close to 100 bugs in DBMSs