# Andrew Trenk Published articles for Andrew Trenk. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Google Renames Testing on the Toilet as Tech on the Toilet DevFeed: [Google Renames Testing on the Toilet as Tech on the Toilet]() Original publisher: [Read original article]() Author: Google Testing Bloggers (noreply@blogger.com) Published: 2024-12-03T13:34:00Z Content type: article Language: en Sources: [Google Testing Blog]() Topics: [Development](), [Software Engineering](), [Testing](), [Google]() Tags: [andrew-trenk](), [development](), [kanu-tewary](), [software](), [software-development](), [software-engineering](), [software-testing](), [tech](), [tott]() ### AI overview Google's weekly Tech on the Toilet publication has been renamed from Testing on the Toilet to reflect its broader coverage of software development topics, including coding practices, machine learning, and web development. ### Source excerpt By Kanu Tewary and Andrew Trenk Tech on the Toilet (TotT) is a weekly one-page publication about software development that is posted in bathrooms in Google offices worldwide. At Google, TotT is a trusted source for high quality technical content and software engineering best practices. TotT episodes relevant outside Google are posted to this blog. We have been posting TotT to this blog since 2007. We're excited to announce that Testing on the Toilet has been renamed Tech on the Toilet. TotT originally covered only software testing topics, but for many years has been covering any topics relevant to software development, such as coding practices, machine learning, web development, and more. A Cultural Institution TotT is a grassroots effort with a mission to deliver easily-digestable one-pagers on software development to engineers in the most unexpected of places: bathroom stalls! But TotT is more than just bathroom reading -- it's a movement. Driven by a team of 20-percent volunteers, TotT empowers Google employees to learn and grow, fostering a culture of excellence within the Google engineering community. Photos of TotT posted in bathroom stalls at Google. Anyone at Google can author a TotT episode (regardless of tenure or seniority). Each episode is carefully curated and edited to provide concise, actionable, authoritative information about software best practices and developer tools. After an episode is published, it is posted to Google bathrooms around the world, and is also available to read online internally at Google. TotT episodes often become a canonical source for helping far-flung teams standardize their software development tools and practices. Because Every Superhero Has An Origin Story TotT began as a bottom-up approach to drive a culture change. The year was 2006 and Google was experiencing rapid growth and huge challenges: there were many costly bugs and rolled-back releases. A small group of engineers, members of the so-called Testing Grouplet, pass ## Increase Test Fidelity By Avoiding Mocks DevFeed: [Increase Test Fidelity By Avoiding Mocks]() Original publisher: [Read original article]() Author: Google Testing Bloggers (noreply@blogger.com) Published: 2024-02-27T18:43:00Z Content type: tutorial Language: en Sources: [Google Testing Blog]() Topics: [Testing](), [Mocking](), [Software Engineering](), [Database](), [API]() Tags: [andrew-trenk](), [article](), [bugs](), [code](), [database](), [dillon-bly](), [in-memory-database](), [software](), [software-engineering](), [testing](), [tests](), [tott](), [unit-tests]() ### AI overview This Google Testing on the Toilet article explains that test fidelity is higher when tests use the real dependency implementation. If that is impractical, it recommends using a fake, such as an in-memory database, and using a mock only when neither a real implementation nor a fake is suitable. Mocks can reduce fidelity because their inline behavior may diverge from the real dependency. ### Source excerpt This article was adapted from a Google Testing on the Toilet (TotT) episode. You can download a printer-friendly version of this TotT episode and post it in your office. By Andrew Trenk and Dillon Bly Replacing your code's dependencies with mocks can make unit tests easier to write and faster to run. However, among other problems, using mocks can lead to tests that are less effective at catching bugs. The fidelity of a test refers to how closely the behavior of the test resembles the behavior of the production code. A test with higher fidelity gives you higher confidence that your code will work properly. When specifying a dependency to use in a test, prefer the highest-fidelity option. Learn more in the Test Doubles chapter of the Software Engineering at Google book. Try to use the real implementation. This provides the most fidelity, because the code in the implementation will be executed in the test. There may be tradeoffs when using a real implementation: they can be slow, non-deterministic, or difficult to instantiate (e.g., it connects to an external server). Use your judgment to decide if a real implementation is the right choice. Use a fake if you can't use the real implementation. A fake is a lightweight implementation of an API that behaves similarly to the real implementation, e.g., an in-memory database. A fake ensures a test has high fidelity, but takes effort to write and maintain; e.g., it needs its own tests to ensure that it conforms to the behavior of the real implementation. Typically, the owner of the real implementation creates and maintains the fake. Use a mock if you can't use the real implementation or a fake. A mock reduces fidelity, since it doesn't execute any of the actual implementation of a dependency; its behavior is specified inline in a test (a technique known as stubbing), so it may diverge from the behavior of the real implementation. Mocks provide a basic level of confidence that your code works properly, and can be especially use