Compare UndercoverCI vs. evalship

Enhance your Ruby testing and GitHub experience with actionable coverage insights that allow your team to deliver robust code efficiently while minimizing the time spent on pull request assessments. Rather than striving for a perfect 100% test coverage, focus on decreasing defects in your pull requests by identifying untested code changes before they go live. After a straightforward setup where the CI server runs tests and sends coverage results to UndercoverCI, you can ensure that every pull request is meticulously examined; we analyze the changes in your code and assess local test coverage for each modified class, method, and block, as merely knowing the overall percentage is insufficient. This tool uncovers untested methods and blocks, highlights unused code paths, and aids in refining your test suite. You can easily integrate UndercoverCI's hosted GitHub App or dive into the array of Ruby gems available. With a fully-featured integration for code review through GitHub, setup is quick and tailored for your organization’s needs. Moreover, the UndercoverCI initiative and its associated Ruby gems are completely open-source and can be utilized freely in your local environment and throughout your CI/CD processes, making it a versatile choice for any development team. By adopting UndercoverCI, you not only improve your code quality but also foster a culture of continuous improvement within your team.

Evalship assists engineering teams in assessing LLM-driven software by conducting evaluation-suite audits and reviewing pull requests. It meticulously examines scorers and judges for potential errors, spots areas lacking coverage, and highlights evaluations that might yield incorrect outcomes, all while presenting findings complete with code references and recommendations for improvements. The setup process aids a coding agent in configuring GitHub Actions and initiating a setup pull request. For subsequent pull requests, evalship analyzes the outcomes in relation to the default branch, identifying regressions, flaky evaluations, and any modifications to prompts or model calls that lack evaluation coverage, alongside offering a merge-gating status check. It processes results from various supported test runners and LLM evaluation platforms. Evaluations are executed within the customer’s GitHub Actions environment using their specific model API keys, while evalship focuses on reviewing these results rather than carrying out the evaluations itself. In addition to these features, teams can access their evaluation history and obtain weekly performance reports to track progress and improvements over time. This comprehensive approach ensures that software quality remains a top priority throughout the development lifecycle.