Quality & Validation
Chairs: Olga Mierzwa-Sulima, Eric Nantz and Paulo Bargo
See also: 2023 Discussion, 2024 Discussion
Shiny-Centric Validation Discussion
- Dynamic Validation: Challenges validating Shiny apps with multiple inputs and dynamic UI changes
- Cross-Language Validation: Interesting approach using different languages (e.g., SAS) to validate Shiny outputs
- User-Centric Testing: Need for dynamic validation of user interactions beyond business logic validation
Package Validation Approaches
- Environment Types: Companies building both exploratory and validated GXP environments
- Validation Cycles: Range from every 6-12 months to agile approaches completing validation in hours
- Speed vs. Compliance: Demonstration that speed and compliance can coexist with proper processes
Infrastructure Management
- Container Strategy:
- Managing multiple packages and images is challenging
- Base images specific to projects or therapeutic areas recommended
- Kubernetes as standard for container management
- Container sizing remains technical challenge
- Image Management: Need for structured approach to container proliferation
Package Transparency Benefits
- Open Source Advantage: Unlike SAS, can see how bugs are identified and resolved
- Visibility: Access to bug reports and fixes provides better understanding than closed-source alternatives
- Internal Package Standards: Internal packages should follow same validation processes as external packages
Testing Standards and Practices
- Separation of Roles: Testers should be different from developers
- Validation Definitions: No industry standard for what “validated package” means - companies define their own criteria
- Reproducibility: Focus on reproducible code as foundation for validation
GenAI Integration Challenges
- Output Validation: GenAI outputs need reproducible code that can be tested and validated
- Documentation Transparency: Suggestion to identify AI-generated documentation for additional scrutiny
- AI-Assisted Review: Mixed opinions on using AI bots to evaluate tests - could be useful but may reduce human vigilance
Emerging Tools and Technologies
- Testing Innovation: New automated testing tools with reporting and screenshots coming from vendors
- ShinyTest Evolution: Improvements in Shiny testing capabilities
- Teal vs. ShinyMeta: Teal’s approach to reproducible scripts gaining more adoption than ShinyMeta
- DuckDB Integration: Promising for handling large data in Shiny applications without full database overhead
Backward Compatibility
- R Perception vs. Reality: Addressing misconceptions about R’s backward compatibility
- Documentation Needs: Importance of documenting package versioning and major changes