System Architecture Overview

Core Components

• Data Processing Engine: Python-based module for extracting and comparing PA calibration parameters
• Validation Framework: pytest integration with custom test cases for automated verification
• Reporting System: Allure Report generation for comprehensive test evidence

Technical Stack

Input File Specifications

Required Files

File Processing Logic

# Example file processing implementation
class FileProcessor:
    def __init__(self, input_dir):
        self.input_dir = input_dir
        
    def extract_hardware_info(self):
        pid_pattern = r'"([^"]+)"'
        for file in os.listdir(self.input_dir):
            if file.startswith('sys_hw_pid'):
                with open(file) as f:
                    match = re.search(pid_pattern, f.read())
                    return match.group(1) if match else None

Validation Workflow

1. Data Extraction Phase

   • Parse binary database to text format
   • Extract calibration parameters from multiple sources
   • Convert measurement units for comparison

2. Comparison Phase

   • Match parameters by VDD ID and transistor index
   • Implement tolerance thresholds for numerical values
   • Handle missing data scenarios

3. Reporting Phase

   • Generate detailed HTML reports with visual diffs
   • Categorize findings by severity
   • Preserve raw data for audit purposes

Test Case Implementation

Parameter Validation Example

@pytest.mark.parametrize('vdd_id,transistor', test_cases)
def test_target_values(vdd_id, transistor):
    expected = get_expected_value(vdd_id, transistor)
    actual = get_actual_value(vdd_id, transistor)
    
    with subtests.test(f'VDD{vdd_id}.{transistor}'):
        assert abs(expected - actual) <= tolerance, \
               f'Mismatch: expected {expected}, got {actual}'

GUI Enterface Features

• Dynamic test case selection with filtering
• Real-time progress monitoring
• Interactive report viewing
• Export functionality for test results

Output Generation

• Structured JSON intermediate files
• HTML reports with drill-down capabilities
• Machine-readable test summaries
• Historical comparison data

Deployment Configuration

• Standalone executable via PyInstaller
• Custom icon and branding
• Automated dependancy resolution
• Silent installation options