Skip to content

10. Quality Requirements (MVP)

10.1 MVP Quality Goals

Quality goals are defined in Section 1.2. This section details how they are measured and implemented.

MVP Quality Priorities

Priority Quality Goal MVP Scenario Measurability
1 Rapid Development MVP deliverable in 5 weeks Functional prototype
2 Simulation Accuracy & Reliability Same inputs → identical results Reproducible simulation runs
3 Usability & Accessibility No complex installation File-based configuration
4 Simple Installation One-command setup uv sync
5 Testability Business logic isolated Unit tests possible

10.2 MVP Performance Requirements

Note: Performance targets will be measured during MVP implementation. See Section 7.8 for monitoring approach.

MVP Performance Goals

graph TB
    subgraph "MVP Performance Goals"
        subgraph "Execution Time"
            Config[Load configuration<br/>To be measured]
            Setup[Configure workshop<br/>To be measured]
            Sim[Simulation execution<br/>To be measured]
            Output[Generate output<br/>To be measured]
        end

        subgraph "Resource Usage"
            Memory[Memory usage<br/>To be measured]
            CPU[CPU utilization<br/>Single-threaded]
            Disk[Disk space<br/>Estimated: ~100 MB + results]
        end

        subgraph "Scalability"
            Small[100 wagons<br/>To be measured]
            Medium[1000 wagons<br/>To be measured]
            Large[5000 wagons<br/>To be measured]
        end
    end

    classDef time fill:#e3f2fd
    classDef resource fill:#e8f5e8
    classDef scale fill:#fff3e0

    class Config,Setup,Sim,Output time
    class Memory,CPU,Disk resource
    class Small,Medium,Large scale

MVP Performance Measurements

Metric Measurement Method Acceptance Criterion
Startup time time python main.py --help To be measured on standard laptop
Configuration loading Logging timestamps JSON/CSV parsing
Simulation speed SimPy profiling Discrete event processing
Memory usage psutil monitoring To be measured
Output generation File creation time CSV + PNG generation

10.3 MVP Usability Requirements

MVP Usability Goals

graph TB
    subgraph "MVP Usability Goals"
        subgraph "Ease of Use"
            Install[Simple installation<br/>uv sync]
            Config[Simple configuration<br/>JSON/CSV files]
            Run[Simple execution<br/>uv run python main.py]
        end

        subgraph "Error Handling"
            Clear[Clear error messages<br/>Actionable feedback]
            Recovery[Graceful degradation<br/>Partial results on error]
            Help[Built-in help<br/>--help parameter]
        end

        subgraph "Output Quality"
            Readable[Readable output<br/>CSV format]
            Visual[Visualization<br/>Matplotlib PNG]
            Logs[Detailed logs<br/>Debugging information]
        end
    end

    classDef ease fill:#4caf50,stroke:#2e7d32
    classDef error fill:#ff9800,stroke:#e65100
    classDef output fill:#2196f3,stroke:#1565c0

    class Install,Config,Run ease
    class Clear,Recovery,Help error
    class Readable,Visual,Logs output

MVP Usability Criteria

Aspect MVP Requirement Measurement Criterion
Installation Simple setup Documented steps
Configuration Example files available Template files in Data/examples/
Execution One command starts simulation uv run python main.py
Error messages Understandable descriptions Pydantic comprehensive error summary
Help Integrated documentation --help parameter

10.4 MVP Reliability Requirements

MVP Reliability Goals

graph TB
    subgraph "MVP Reliability"
        subgraph "Error Tolerance"
            InputErrors[Input validation<br/>Catch invalid data]
            RuntimeErrors[Runtime stability<br/>No crashes during simulation]
            OutputErrors[Output robustness<br/>Partial results on error]
        end

        subgraph "Determinism"
            Reproducible[Reproducible results<br/>Same input → same output]
            Seeded[Seeded random<br/>Controlled randomness]
            Consistent[Consistent behavior<br/>Cross-platform]
        end

        subgraph "Recovery"
            Logging[Comprehensive logging<br/>Debug information]
            Cleanup[Resource cleanup<br/>No memory leaks]
            Restart[Easy restart<br/>No persistent state issues]
        end
    end

    classDef tolerance fill:#e3f2fd
    classDef determinism fill:#e8f5e8
    classDef recovery fill:#fff3e0

    class InputErrors,RuntimeErrors,OutputErrors tolerance
    class Reproducible,Seeded,Consistent determinism
    class Logging,Cleanup,Restart recovery

MVP Reliability Metrics

Category MVP Goal Measurement Method
Crash rate < 1% with valid inputs Automated tests
Determinism 100% identical results Repeated execution with same inputs
Error handling Graceful handling of all input errors Negative tests
Memory leaks No memory leaks Memory profiling

10.5 MVP Maintainability Requirements

MVP Code Quality Standards

# MVP Code Quality Standards
class CodeQualityMetrics:
    MAX_FUNCTION_LENGTH = 50      # Lines per function
    MAX_CLASS_LENGTH = 200        # Lines per class
    MAX_COMPLEXITY = 10           # Cyclomatic complexity
    MIN_TEST_COVERAGE = 90        # Percent
    MAX_DEPENDENCIES = 5          # Per module

MVP Maintainability Metrics

Aspect MVP Goal Measurement Method
Code coverage > 90% for business logic pytest-cov
Documentation All public APIs documented Docstring coverage
Complexity Cyclomatic complexity < 10 radon
Dependencies < 10 external packages pyproject.toml
Refactoring Easy extension possible Architecture review

10.6 MVP Portability Requirements

MVP Platform Support

graph TB
    subgraph "MVP Platform Support"
        subgraph "Operating Systems"
            Windows[Windows 10+<br/>Primary target]
            MacOS[macOS 10.15+<br/>Primary target]
            Linux[Ubuntu 20.04+<br/>Primary target]
        end

        subgraph "Python Versions"
            Python313[Python 3.13+<br/>Required]
        end

        subgraph "Hardware"
            Laptop[Standard laptop<br/>Estimated: 4GB RAM minimum]
            Desktop[Desktop PC<br/>Estimated: 4GB RAM minimum]
        end
    end

    classDef primary fill:#4caf50,stroke:#2e7d32
    classDef secondary fill:#ff9800,stroke:#e65100
    classDef hardware fill:#2196f3,stroke:#1565c0

    class Windows,MacOS,Linux,Python313 primary
    class Laptop,Desktop hardware

MVP Portability Tests

Platform Test Status Critical Features
Windows 10+ ✅ Primary File paths, CSV encoding
macOS 10.15+ ✅ Primary Path separators, matplotlib
Ubuntu 20.04+ ✅ Primary Dependencies, file permissions

10.7 MVP Security Requirements

MVP Security Goals

graph TB
    subgraph "MVP Security"
        subgraph "Input Security"
            Validation[Input validation<br/>Pydantic models]
            Sanitization[Path sanitization<br/>No directory traversal]
            Limits[Resource limits<br/>File size, memory]
        end

        subgraph "Data Security"
            NoCredentials[No credentials<br/>No sensitive data stored]
            LocalOnly[Local processing<br/>No network communication]
            TempFiles[Safe temp files<br/>Proper cleanup]
        end

        subgraph "Error Security"
            NoLeakage[No information leakage<br/>Safe error messages]
            Logging[Safe logging<br/>No sensitive data in logs]
        end
    end

    classDef input fill:#e3f2fd
    classDef data fill:#e8f5e8
    classDef error fill:#fff3e0

    class Validation,Sanitization,Limits input
    class NoCredentials,LocalOnly,TempFiles data
    class NoLeakage,Logging error

MVP Security Measures

Area MVP Measure Implementation
Input validation Pydantic models Automatic type validation
File access Relative paths only Path sanitization
Error handling Safe error messages No system paths in errors
Logging No sensitive data Filtered logging
Dependencies Known packages only pyproject.toml with versions

10.8 MVP Testability Requirements

MVP Test Strategy

graph TB
    subgraph "MVP Testing Strategy"
        subgraph "Unit Tests"
            Models[Domain Models<br/>Business Logic]
            Services[Service classes<br/>Isolated testing]
            Utils[Utility functions<br/>Pure functions]
        end

        subgraph "Integration Tests"
            FileIO[File I/O<br/>JSON/CSV processing]
            SimPy[SimPy integration<br/>Simulation engine]
            EndToEnd[End-to-end<br/>Complete scenarios]
        end

        subgraph "Manual Tests"
            Scenarios[Test scenarios<br/>Real configurations]
            Performance[Performance tests<br/>Large datasets]
            Platforms[Platform tests<br/>Cross-platform]
        end
    end

    classDef unit fill:#4caf50,stroke:#2e7d32
    classDef integration fill:#ff9800,stroke:#e65100
    classDef manual fill:#9e9e9e,stroke:#616161

    class Models,Services,Utils unit
    class FileIO,SimPy,EndToEnd integration
    class Scenarios,Performance,Platforms manual

MVP Test Metrics

Test Type MVP Goal Automation
Unit tests > 80% coverage ✅ pytest
Integration tests All main paths ✅ pytest
Performance tests Benchmark scenarios ⚠️ Manual
Platform tests Windows + Linux + macOS ⚠️ Manual (can be automated via GitHub Actions matrix)