{
  "format": "attestql/audit/smells/2",
  "reading": "A smell is a mechanical reason to read this gold statement again. It is a heuristic: it does not state that the statement is wrong, and a maintainer decides.",
  "smells": [
    {
      "name": "ordering-over-numeric-text",
      "fired": false,
      "applicable": false,
      "evidence": {
        "heuristic": true,
        "means": "this statement orders by a text column holding only numbers, and ordering it as a number gives a different answer, so the gold may be sorting 9.5 above 10",
        "reason": "no ORDER BY key resolves to a text column",
        "keys": [
          {
            "key": "T3.cost",
            "column": "expense.cost",
            "declared_type": "REAL",
            "not_applicable": "the column is not declared as text"
          }
        ]
      },
      "counterexample_rows": []
    },
    {
      "name": "arbitrary-cut",
      "fired": true,
      "applicable": true,
      "evidence": {
        "heuristic": true,
        "means": "this statement cuts its result at a LIMIT that does not decide which rows come back, so a different but equally correct statement can return other rows and score zero",
        "cut": 1,
        "offset": 0,
        "distinct_kept": false,
        "unbounded_sql": "SELECT T1.event_name, T3.cost AS attestql_ordering_key_0 FROM event AS T1 INNER JOIN budget AS T2 ON T1.event_id = T2.link_to_event INNER JOIN expense AS T3 ON T2.budget_id = T3.link_to_budget ORDER BY T3.cost",
        "unbounded_rows": 32,
        "projected_columns": [
          "event_name"
        ],
        "ordering_key_columns": [
          "attestql_ordering_key_0"
        ],
        "ordering_keys": [
          {
            "key": "T3.cost",
            "direction": "asc",
            "nulls": "first",
            "nulls_first_in_effect": true,
            "returned_rows_null_in_this_key": 0,
            "fires": false
          }
        ],
        "tied_at_the_cut": {
          "positions": [
            0,
            1,
            2
          ],
          "tied_rows": 3,
          "distinct_projected_answers": 3,
          "rows": [
            [
              {
                "type": "str",
                "value": "November Speaker"
              }
            ],
            [
              {
                "type": "str",
                "value": "October Speaker"
              }
            ],
            [
              {
                "type": "str",
                "value": "September Speaker"
              }
            ]
          ]
        },
        "case": "tie-at-the-cut"
      },
      "counterexample_rows": [
        [
          {
            "type": "str",
            "value": "November Speaker"
          },
          {
            "type": "dec",
            "value": "6.0"
          }
        ],
        [
          {
            "type": "str",
            "value": "October Speaker"
          },
          {
            "type": "dec",
            "value": "6.0"
          }
        ],
        [
          {
            "type": "str",
            "value": "September Speaker"
          },
          {
            "type": "dec",
            "value": "6.0"
          }
        ]
      ]
    },
    {
      "name": "not-a-function-of-the-data",
      "fired": false,
      "applicable": true,
      "evidence": {
        "heuristic": true,
        "means": "rerun over the same rows in another physical order this statement gives another answer, so its result depends on how the rows are stored and not only on the data",
        "rule": "R-ORD",
        "baseline_result_hash": "sha256:a64abae025d48878b3159093c209dd31eb9109bb35fef916a1b99a270439cda2",
        "baseline_result": {
          "columns": [
            {
              "name": "event_name",
              "declared_type": "TEXT"
            }
          ],
          "row_count": 1,
          "truncated": false,
          "rows_shown": 1,
          "rows": [
            [
              {
                "type": "str",
                "value": "November Speaker"
              }
            ]
          ],
          "result_hash": "sha256:a64abae025d48878b3159093c209dd31eb9109bb35fef916a1b99a270439cda2"
        },
        "planner_statistics": {},
        "shuffle": {
          "seed": "1",
          "row_limit": 300000,
          "tables": [
            "event",
            "budget",
            "expense"
          ],
          "tables_not_shuffled": [],
          "tables_skipped_for_size": {},
          "tables_not_reached_by_a_copy": {}
        },
        "shuffled_copies": {
          "run": true,
          "verdict": "equal",
          "differs": false,
          "result_hash": "sha256:a64abae025d48878b3159093c209dd31eb9109bb35fef916a1b99a270439cda2",
          "result": {
            "columns": [
              {
                "name": "event_name",
                "declared_type": "TEXT"
              }
            ],
            "row_count": 1,
            "truncated": false,
            "rows_shown": 1,
            "rows": [
              [
                {
                  "type": "str",
                  "value": "November Speaker"
                }
              ]
            ],
            "result_hash": "sha256:a64abae025d48878b3159093c209dd31eb9109bb35fef916a1b99a270439cda2"
          }
        },
        "plan_variant": {
          "run": false,
          "reason": "the plan variant was not asked for"
        }
      },
      "counterexample_rows": []
    }
  ]
}