When working with beginner developers, one challenge that often comes up is understanding what constitutes “junk data” versus “seed data.” I encountered this distinction recently when a new developer submitted their first pull request, which included several JSON files they’d generated during local testing. We had a conversation about whether these files should actually be checked in, which led to a broader discussion about the role of seed data and what separates it from random artifacts of local testing.

In this case, the developer initially thought these files might qualify as seed data. However, as we discussed some guiding principles, it became clear that this wasn’t the case. Seed data is something intentionally crafted to enable specific, crucial scenarios that would otherwise be unavailable out of the box. It should eliminate significant setup work for new developers, ideally providing them with a head start by avoiding repetitive configuration tasks.

  1. Purposeful Design for Key Scenarios: Seed data should be explicitly crafted to support specific, essential scenarios that won’t work out of the box without it. It isn’t just any test data — it’s intentional and carefully structured to exercise key features or workflows within the application.
  2. Reduce Onboarding Toil: Seed data should significantly reduce setup time for new developers, allowing them to get up and running faster. If it helps avoid repetitive setup tasks or clears initial configuration hurdles, it’s more likely to be beneficial seed data.

Thinking through these criteria, the developer and I realized that their JSON files fell short of this standard.

First, they weren’t thoughtfully designed to exercise key scenarios in our software; rather, they were created haphazardly as a byproduct of whatever testing the developer happened to be doing at the time. Second, they also didn’t meaningfully reduce setup time or alleviate configuration hurdles for future developers. In fact, the data represented here was simply the type of information that would typically be generated through normal use of the software, rather than serving as a foundation for testing core functionality.

One important point I always emphasize with new developers is being mindful of the kinds of files we’re committing to our repositories. Aside from avoiding files with secrets, it’s crucial to distinguish between valuable artifacts and extraneous “junk” data.

Seed data has a specific purpose: it’s embedded to exercise the most essential scenarios our software needs to cover and should include instructions if additional setup is required. If creating or including seed data involves less effort than manually reproducing it each time, then it might be worth including. Otherwise, runtime artifacts — especially those not explicitly crafted to support key scenarios — are likely better left uncommitted. Developing this discernment is key to understanding when data adds value to a project and when it’s simply noise.

If we have decided that we want to include actual “Seed Data” then we should ensure we put in place necessary documentation to help new developers onboard and use this seed data within their environment. This could be manual steps or automation that’s part of the environment setup process.

In summary, understanding the difference between junk data and seed data is essential for maintaining a clean, functional codebase, especially as developers grow into team-based workflows. Seed data has a specific purpose: it enables key scenarios and makes setup easier for others, reducing unnecessary toil and providing a well-thought-out starting point for core application functions. Junk data, on the other hand, is simply the residue of local testing — useful in the moment (to a specific developer) but ultimately clutter in the repository.

By following these principles, new developers can make informed decisions about what to commit and what to leave out, supporting a codebase that is both organized and welcoming for new team members.