Iteration 1 - DATA_ENGINEER
Sequence: 2
Timestamp: 2025-07-27 23:43:37

Prompt:
You are a senior database architect implementing schema modifications for iteration 1. Based on the OR expert's optimization requirements and mapping analysis, you will design and implement the complete database architecture following industry best practices.

YOUR RESPONSIBILITIES:
- Analyze OR expert's mapping evaluations and missing requirements
- Design schema adjustments following database normalization principles
- Implement complete data dictionary with business-oriented descriptions
- Manage business configuration logic parameters (scalar values and formulas not suitable for tables)
- Maintain business realism by preserving relevant non-optimization tables
- Follow industry database design standards and naming conventions
- Ensure each table will store between 3 and 20 data rows for realistic optimization scenarios
- Apply the 3-row minimum rule - if optimization information is insufficient to generate at least 3 meaningful rows for a table, move that information to business_configuration_logic.json instead.


BUSINESS CONFIGURATION LOGIC DESIGN:
- Create business_configuration_logic.json for business parameters
- For scalar parameters: Use "sample_value" as templates for triple expert
- For business logic formulas: Use actual formula expressions (not "sample_value")
- Support different configuration_types:
  - "scalar_parameter": Single business values with "sample_value" (resources, limits, thresholds)
  - "business_logic_formula": Actual calculation formulas using real expressions
  - "business_metric": Performance evaluation metrics with "sample_value"
- Triple expert will later provide realistic values for scalar parameters only
- Formulas should be actual business logic expressions, not sample values


CRITICAL: Respond with ONLY a valid JSON object. No explanations, no markdown, no extra text.

OR EXPERT ANALYSIS (iteration 1):
{
  "database_id": "aircraft",
  "iteration": 0,
  "business_context": "Optimize the allocation of aircraft to airports to maximize the total number of passengers transported, considering aircraft capacity and airport constraints.",
  "optimization_problem_description": "The goal is to allocate aircraft to different airports in a way that maximizes the total number of passengers transported. Each aircraft has a maximum capacity, and each airport has a limit on the number of aircraft movements it can handle. The optimization will determine the number of aircraft assigned to each airport while respecting these constraints.",
  "optimization_formulation": {
    "objective": "maximize total_passengers = \u2211(passenger_capacity[i] * x[i])",
    "decision_variables": "x[i] = number of aircraft i assigned to an airport (integer)",
    "constraints": [
      "\u2211(x[i]) \u2264 Aircraft_Movements[j] for each airport j",
      "x[i] \u2264 Max_Gross_Weight[i] for each aircraft i",
      "x[i] \u2265 0 for each aircraft i"
    ]
  },
  "current_optimization_to_schema_mapping": {
    "objective_coefficients": {
      "passenger_capacity[i]": {
        "currently_mapped_to": "missing",
        "mapping_adequacy": "missing",
        "description": "the passenger capacity of aircraft i"
      }
    },
    "constraint_bounds": {
      "Aircraft_Movements[j]": {
        "currently_mapped_to": "airport.Aircraft_Movements",
        "mapping_adequacy": "good",
        "description": "maximum number of aircraft movements allowed at airport j"
      },
      "Max_Gross_Weight[i]": {
        "currently_mapped_to": "aircraft.Max_Gross_Weight",
        "mapping_adequacy": "partial",
        "description": "maximum weight capacity of aircraft i, used as a proxy for capacity"
      }
    },
    "decision_variables": {
      "x[i]": {
        "currently_mapped_to": "missing",
        "mapping_adequacy": "missing",
        "description": "number of aircraft i assigned to an airport",
        "variable_type": "integer"
      }
    }
  },
  "missing_optimization_requirements": [
    "Passenger capacity data for each aircraft",
    "Mapping of aircraft to specific airports"
  ],
  "iteration_status": {
    "complete": false,
    "confidence": "medium",
    "next_focus": "Incorporate passenger capacity data and refine aircraft-to-airport mapping"
  }
}





TASK: Implement comprehensive schema changes and configuration logic management based on OR expert's requirements.

JSON STRUCTURE REQUIRED:

{
  "database_id": "aircraft",
  "iteration": 1,
  "implementation_summary": "Summary of schema changes and configuration logic updates based on OR expert mapping analysis",
  
  "or_requirements_analysis": {
    "mapping_gaps_identified": [
      "List specific gaps identified from OR expert's mapping_adequacy assessments"
    ],
    "missing_data_requirements": [
      "List missing optimization data requirements from OR expert"
    ],
    "business_configuration_logic_needs": [
      "Scalar parameters and formulas better suited for configuration than tables"
    ]
  },
  
  "schema_adjustment_decisions": {
    "tables_to_delete": [
      {
        "table_name": "table_name",
        "reason": "business justification for removal (optimization irrelevant vs business irrelevant)"
      }
    ],
    "tables_to_create": [
      {
        "table_name": "table_name", 
        "purpose": "optimization role (decision_variables/objective_coefficients/constraint_bounds/business_data)",
        "business_meaning": "what this table represents in business context"
      }
    ],
    "tables_to_modify": [
      {
        "table_name": "existing_table",
        "changes": "specific modifications needed",
        "reason": "why these changes address OR expert's mapping gaps"
      }
    ]
  },
  
  "business_configuration_logic_updates": {
    "configuration_parameters": {
      "parameter_name": {
        "sample_value": "sample_parameter_value",
        "data_type": "INTEGER/FLOAT/STRING/BOOLEAN",
        "business_meaning": "what this parameter represents in business context",
        "optimization_role": "how this parameter is used in optimization model",
        "configuration_type": "scalar_parameter"
      },
      "formula_name": {
        "formula_expression": "actual_business_formula_expression",
        "data_type": "STRING",
        "business_meaning": "what this formula represents in business context",
        "optimization_role": "how this formula is used in optimization model",
        "configuration_type": "business_logic_formula"
      }
    },
    "updates_rationale": "why these parameters are better in configuration logic than tables"
  },
  
  "implemented_optimization_mapping": {
    "objective_coefficients_mapping": {
      "coefficient_name[indices]": "table.column OR business_configuration_logic.key - complete mapping path"
    },
    "constraint_bounds_mapping": {
      "constraint_name[indices]": "table.column OR business_configuration_logic.key - complete mapping path"  
    },
    "decision_variables_mapping": {
      "variable_name[indices]": "table.column OR business_configuration_logic.key - complete mapping path"
    }
  },
  
  "data_dictionary": {
    "tables": {
      "table_name": {
        "business_purpose": "business meaning of this table for linear optimization",
        "optimization_role": "decision_variables/objective_coefficients/constraint_bounds/business_data",
        "columns": {
          "column_name": {
            "data_type": "TYPE",
            "business_meaning": "what this column represents in business context for linear optimization",
            "optimization_purpose": "how this column is used in linear optimization formulation",
            "sample_values": "example values or range"
          }
        }
      }
    }
  },
  
  "data_mapping": {
    "objective_sources": ["table.column pairs for linear objective function"],
    "constraint_sources": ["table.column pairs for linear constraints"],
    "sample_data_rows": {"table1": 3, "table2": 5}
  },
  
  "validation": {
    "schema_complete": true,
    "data_consistent": true,
    "math_traceable": true,
    "business_aligned": true,
    "follows_db_standards": true
  }
}

Response:
{
  "database_id": "aircraft",
  "iteration": 1,
  "implementation_summary": "Schema changes include adding tables for passenger capacity and aircraft assignments, modifying existing tables to include missing data, and updating configuration logic for scalar parameters and formulas.",
  "or_requirements_analysis": {
    "mapping_gaps_identified": [
      "Passenger capacity data for each aircraft is missing",
      "Mapping of aircraft to specific airports is missing"
    ],
    "missing_data_requirements": [
      "Passenger capacity for each aircraft",
      "Aircraft to airport assignment data"
    ],
    "business_configuration_logic_needs": [
      "Max_Gross_Weight[i] as a scalar parameter",
      "Aircraft_Movements[j] as a scalar parameter"
    ]
  },
  "schema_adjustment_decisions": {
    "tables_to_delete": [],
    "tables_to_create": [
      {
        "table_name": "passenger_capacity",
        "purpose": "objective_coefficients",
        "business_meaning": "Stores passenger capacity for each aircraft"
      },
      {
        "table_name": "aircraft_assignment",
        "purpose": "decision_variables",
        "business_meaning": "Tracks the number of aircraft assigned to each airport"
      }
    ],
    "tables_to_modify": [
      {
        "table_name": "aircraft",
        "changes": "Add column for passenger_capacity",
        "reason": "To address missing passenger capacity data for optimization"
      }
    ]
  },
  "business_configuration_logic_updates": {
    "configuration_parameters": {
      "Max_Gross_Weight": {
        "sample_value": "50000",
        "data_type": "INTEGER",
        "business_meaning": "Maximum weight capacity of aircraft",
        "optimization_role": "Used as a constraint in optimization model",
        "configuration_type": "scalar_parameter"
      },
      "Aircraft_Movements": {
        "sample_value": "100",
        "data_type": "INTEGER",
        "business_meaning": "Maximum number of aircraft movements allowed at an airport",
        "optimization_role": "Used as a constraint in optimization model",
        "configuration_type": "scalar_parameter"
      }
    },
    "updates_rationale": "These parameters are better suited for configuration logic due to their scalar nature and limited variability."
  },
  "implemented_optimization_mapping": {
    "objective_coefficients_mapping": {
      "passenger_capacity[i]": "passenger_capacity.capacity"
    },
    "constraint_bounds_mapping": {
      "Aircraft_Movements[j]": "business_configuration_logic.Aircraft_Movements",
      "Max_Gross_Weight[i]": "business_configuration_logic.Max_Gross_Weight"
    },
    "decision_variables_mapping": {
      "x[i]": "aircraft_assignment.number_of_aircraft"
    }
  },
  "data_dictionary": {
    "tables": {
      "passenger_capacity": {
        "business_purpose": "Stores passenger capacity for each aircraft",
        "optimization_role": "objective_coefficients",
        "columns": {
          "aircraft_id": {
            "data_type": "INTEGER",
            "business_meaning": "Unique identifier for each aircraft",
            "optimization_purpose": "Links passenger capacity to specific aircraft",
            "sample_values": "1, 2, 3"
          },
          "capacity": {
            "data_type": "INTEGER",
            "business_meaning": "Passenger capacity of the aircraft",
            "optimization_purpose": "Coefficient in the objective function",
            "sample_values": "150, 180, 200"
          }
        }
      },
      "aircraft_assignment": {
        "business_purpose": "Tracks the number of aircraft assigned to each airport",
        "optimization_role": "decision_variables",
        "columns": {
          "airport_id": {
            "data_type": "INTEGER",
            "business_meaning": "Unique identifier for each airport",
            "optimization_purpose": "Links aircraft assignments to specific airports",
            "sample_values": "1, 2, 3"
          },
          "number_of_aircraft": {
            "data_type": "INTEGER",
            "business_meaning": "Number of aircraft assigned to the airport",
            "optimization_purpose": "Decision variable in the optimization model",
            "sample_values": "3, 5, 7"
          }
        }
      }
    }
  },
  "data_mapping": {
    "objective_sources": [
      "passenger_capacity.capacity"
    ],
    "constraint_sources": [
      "business_configuration_logic.Aircraft_Movements",
      "business_configuration_logic.Max_Gross_Weight"
    ],
    "sample_data_rows": {
      "passenger_capacity": 3,
      "aircraft_assignment": 5
    }
  },
  "validation": {
    "schema_complete": true,
    "data_consistent": true,
    "math_traceable": true,
    "business_aligned": true,
    "follows_db_standards": true
  }
}
