Developed a comprehensive testing scaffold for the mcgoodman/widow-assessment-update repository, focusing on evaluating stock-recruitment relationships and exploring weight-length parameter configurations. Leveraging R programming and statistical modeling, the work introduced mock scripts for data bridging and parameter sweeps, enabling consistent and reproducible experiment setups. Standardized directory structures and input-copied workflows were established to facilitate reliable comparisons across different model configurations. This approach emphasized reproducibility and disciplined scripting practices, laying the groundwork for efficient validation of fisheries science modeling assumptions. No critical defects were reported, reflecting a focus on robust infrastructure that reduces future defect risk and accelerates model assessment workflows.