SQL Test Case Generator and Coverage Visualizer

DataPilot is a powerful tool that automatically generates test cases for SQL queries and visualizes SQL node coverage. It parses SQL statements using Apache Calcite, extracts table/column information, generates intelligent mock data, and tracks which SQL nodes are covered by the test data.

• SQL Parsing: Parse SQL statements using Apache Calcite with support for extensible SQL dialects
• Metadata Extraction: Automatically extract table names, column names, and WHERE conditions
• Smart Mock Data Generation: Generate realistic test data based on column naming conventions
• Coverage Tracking: Track which SQL nodes are covered by generated test data
• Web Interface: Modern, responsive UI for visualization
• Test Script Export: Generate complete INSERT statements and test scripts

• Java 17+
• Maven 3.6+

mvn spring-boot:run

Access the web interface at: http://localhost:9527

curl -X POST http://localhost:9527/api/analyze \
  -H "Content-Type: application/json" \
  -d '{
    "sql": "SELECT id, name, email FROM users WHERE status = 1",
    "rowCount": 5,
    "testCaseCount": 1
  }'

curl http://localhost:9527/api/dialects

DataPilot/
├── parser/           # SQL parsing module
│   ├── SqlDialectProvider.java    # Dialect interface (extensible)
│   ├── StandardSqlDialectProvider.java
│   ├── SqlParserService.java      # Core parsing service
│   └── SqlNodeVisitor.java       # SqlNode traverser
│
├── generator/        # Test data generation module
│   ├── DataType.java            # Data type definition and inference
│   ├── TableSchema.java         # Table structure definition
│   ├── MockDataGenerator.java   # Mock data generator
│   └── TestCase.java            # Test case model
│
├── coverage/         # Coverage tracking module
│   ├── CoverageNode.java        # Coverage node model
│   ├── CoverageResult.java      # Coverage result
│   └── CoverageTracker.java     # Coverage tracker
│
└── controller/       # Web API
    └── DataPilotController.java

DataPilot intelligently infers data types based on column naming conventions:

{
  "success": true,
  "parseResult": {
    "originalSql": "SELECT id, name FROM users WHERE status = 1",
    "dialect": "STANDARD",
    "tableNames": ["users"],
    "columns": [
      {"columnName": "id"},
      {"columnName": "name"}
    ]
  },
  "testCases": [{
    "tableDataMap": {
      "users": {
        "columns": ["id", "name"],
        "rows": [
          {"id": 1, "name": "张伟"},
          {"id": 2, "name": "李芳"}
        ]
      }
    }
  }],
  "coverageResult": {
    "coveragePercentage": 100.0,
    "allNodes": [...],
    "coveredNodeIds": [...]
  },
  "testScript": "-- Test Case for SQL:\nINSERT INTO users..."
}

Implement SqlDialectProvider to add support for custom SQL dialects:

@Component
public class MySqlDialectProvider implements SqlDialectProvider {
    
    @Override
    public String getDialectName() {
        return "MYSQL";
    }
    
    @Override
    public SqlNode parse(String sql) throws SqlParseException {
        SqlParser.Config config = SqlParser.config()
                .withLex(Lex.MYSQL);
        return SqlParser.create(sql, config).parseQuery();
    }
}

• Java 17
• Spring Boot 3.2
• Apache Calcite 1.36 - SQL parsing
• Thymeleaf - Server-side templating
• Lombok - Boilerplate reduction

MIT License