Introducing repscan: Automated detection of Stata commands linked to common reproducibility failures

Reproducibility is essential for understanding how social scientists reach their conclusions. Following recent reproducibility and transparency standards adopted by social science journals, ensuring that code is reproducible has become a priority for researchers and institutions. Reproducibility issues may arise from the use of commands that introduce unnoticed randomness, depend on system-specific settings, or create unexpected inconsistencies across code runs. To address this challenge, the Development Impact Analytics team at the World Bank has developed repscan repscan repscan repscan, a Stata command designed to enhance the reproducibility of research code. Part of the repkit repkit repkit repkit Stata package, repscan repscan repscan repscan scans a do-file, detecting and flagging commands known to compromise reproducibility. By alerting users of potential problems—such as commands affected by uncontrolled randomness, system-dependent sortings, or unstable default behaviors—repscan repscan repscan repscan allows researchers to refine their code and ensure their results can be consistently reproduced. This presentation will provide an overview of repscan repscan repscan repscan’s functionality, demonstrating its application in typical coding tasks and showcasing how it can enhance reproducibility in social science research.