Iteration 1 - DATA_ENGINEER
Sequence: 2
Timestamp: 2025-07-27 23:20:55

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": "musical",
  "iteration": 0,
  "business_context": "A theater company wants to optimize the casting of actors for various musicals to minimize the total age of the cast while ensuring each musical has a complete cast.",
  "optimization_problem_description": "The goal is to assign actors to musicals such that the total age of all actors assigned is minimized. Each musical requires a specific number of actors, and each actor can only be assigned to one musical.",
  "optimization_formulation": {
    "objective": "minimize total_age = \u2211(age[i] * x[i,j])",
    "decision_variables": "x[i,j] = 1 if actor i is assigned to musical j, 0 otherwise (binary)",
    "constraints": [
      "\u2211(x[i,j]) = 1 for each actor i (each actor is assigned to exactly one musical)",
      "\u2211(x[i,j]) = required_actors[j] for each musical j (each musical has the required number of actors)"
    ]
  },
  "current_optimization_to_schema_mapping": {
    "objective_coefficients": {
      "age[i]": {
        "currently_mapped_to": "actor.age",
        "mapping_adequacy": "good",
        "description": "Age of actor i used in the objective function to minimize total age"
      }
    },
    "constraint_bounds": {
      "required_actors[j]": {
        "currently_mapped_to": "missing",
        "mapping_adequacy": "missing",
        "description": "Number of actors required for musical j"
      }
    },
    "decision_variables": {
      "x[i,j]": {
        "currently_mapped_to": "missing",
        "mapping_adequacy": "missing",
        "description": "Binary variable indicating if actor i is assigned to musical j",
        "variable_type": "binary"
      }
    }
  },
  "missing_optimization_requirements": [
    "Number of actors required for each musical",
    "Binary decision variable mapping for actor-musical assignment"
  ],
  "iteration_status": {
    "complete": false,
    "confidence": "medium",
    "next_focus": "Define the number of actors required for each musical and establish binary decision variable mapping"
  }
}





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

JSON STRUCTURE REQUIRED:

{
  "database_id": "musical",
  "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": "musical",
  "iteration": 1,
  "implementation_summary": "Schema changes include creating tables for decision variables and constraint bounds, and updating business configuration logic for scalar parameters and formulas.",
  "or_requirements_analysis": {
    "mapping_gaps_identified": [
      "Missing mapping for number of actors required for each musical",
      "Missing mapping for binary decision variable indicating actor-musical assignment"
    ],
    "missing_data_requirements": [
      "Number of actors required for each musical",
      "Binary decision variable mapping for actor-musical assignment"
    ],
    "business_configuration_logic_needs": [
      "Number of actors required for each musical",
      "Binary decision variable mapping"
    ]
  },
  "schema_adjustment_decisions": {
    "tables_to_delete": [],
    "tables_to_create": [
      {
        "table_name": "musical_requirements",
        "purpose": "constraint_bounds",
        "business_meaning": "Stores the number of actors required for each musical"
      },
      {
        "table_name": "actor_musical_assignment",
        "purpose": "decision_variables",
        "business_meaning": "Stores binary decision variables for actor-musical assignments"
      }
    ],
    "tables_to_modify": []
  },
  "business_configuration_logic_updates": {
    "configuration_parameters": {
      "required_actors": {
        "sample_value": "3",
        "data_type": "INTEGER",
        "business_meaning": "Number of actors required for each musical",
        "optimization_role": "Used as a constraint bound in optimization model",
        "configuration_type": "scalar_parameter"
      }
    },
    "updates_rationale": "Parameters like required_actors are better managed in configuration logic due to their scalar nature and limited data rows."
  },
  "implemented_optimization_mapping": {
    "objective_coefficients_mapping": {
      "age[i]": "actor.age"
    },
    "constraint_bounds_mapping": {
      "required_actors[j]": "business_configuration_logic.required_actors"
    },
    "decision_variables_mapping": {
      "x[i,j]": "actor_musical_assignment.assignment"
    }
  },
  "data_dictionary": {
    "tables": {
      "musical_requirements": {
        "business_purpose": "Defines the number of actors required for each musical",
        "optimization_role": "constraint_bounds",
        "columns": {
          "musical_id": {
            "data_type": "INTEGER",
            "business_meaning": "Unique identifier for each musical",
            "optimization_purpose": "Links to musicals for constraint application",
            "sample_values": "1, 2, 3"
          },
          "required_actors": {
            "data_type": "INTEGER",
            "business_meaning": "Number of actors required for the musical",
            "optimization_purpose": "Constraint bound for actor assignment",
            "sample_values": "3, 4, 5"
          }
        }
      },
      "actor_musical_assignment": {
        "business_purpose": "Tracks which actors are assigned to which musicals",
        "optimization_role": "decision_variables",
        "columns": {
          "actor_id": {
            "data_type": "INTEGER",
            "business_meaning": "Unique identifier for each actor",
            "optimization_purpose": "Links to actors for decision variable",
            "sample_values": "101, 102, 103"
          },
          "musical_id": {
            "data_type": "INTEGER",
            "business_meaning": "Unique identifier for each musical",
            "optimization_purpose": "Links to musicals for decision variable",
            "sample_values": "1, 2, 3"
          },
          "assignment": {
            "data_type": "BOOLEAN",
            "business_meaning": "Indicates if the actor is assigned to the musical",
            "optimization_purpose": "Binary decision variable for optimization",
            "sample_values": "true, false"
          }
        }
      }
    }
  },
  "data_mapping": {
    "objective_sources": [
      "actor.age"
    ],
    "constraint_sources": [
      "musical_requirements.required_actors"
    ],
    "sample_data_rows": {
      "musical_requirements": 3,
      "actor_musical_assignment": 5
    }
  },
  "validation": {
    "schema_complete": true,
    "data_consistent": true,
    "math_traceable": true,
    "business_aligned": true,
    "follows_db_standards": true
  }
}
