2026-03-05 –, RoboCon Online
Do you use an "import everything" file throughout your codebase? Do you encounter maintenance headaches as a result? Do you have good intentions of addressing this but are having trouble making it a priority? This talk moves beyond the theory on why these files are an anti-pattern, and provides strategies and insights from a real-world example of eliminating these global resource files. By leveraging AI, we can reduce the grunt work involved and make this previously overwhelming refactoring challenge much more achievable.
Drawing from a real refactoring project, this talk provides concrete techniques for breaking up global resource files with the assistance of AI.
Topics covered:
- How we got here: Background on why codebases often implement this practice.
- Motivation: Why reducing reliance on global resource files is desired.
- AI memory simulation: Track keyword and variable definitions to aid in import redistribution.
- IDE integration: Combine diagnostic tools with AI to guide refactoring.
- Context management: Handle AI limitations when working across many files.
- Import cleanup: Detect and address unnecessary imports AI may introduce.
- Practical validation: Balance thoroughness with practicality when checking AI output.
Statistics on the codebase size and complexity will be provided, helping participants assess how these approaches will scale to their own projects.
Most importantly, participants will be inspired to tackle similar work in their own codebases.
case study, refactoring, ai, tech debt
Is this suitable for ..?: Intermediate RF User, Advanced RF User Describe your intended audience:This talk is intended for any Robot Framework tester working on an established codebase. It will be most relevant to those who have global resource files. This talk should be suitable for most skill levels, as long as the tester understands the basics of importing resources in Robot Framework files. However, in order to later implement one of the strategies discussed in the presentation, a tester would need familiarity with setting up development containers.
Silken is a Software Tester at SMART Technologies where she has worked on web and mobile automation. She contributes to CI/CD infrastructure and coordinates cross-team automation initiatives. She has experience working with Robot Framework listeners, parsing test results, and customizing reports. She also investigates AI-assisted automation tools, using Claude Code for tasks like multi-repository refactoring and workflow improvements.