See how strong your tests really are—not just how much code they exercise
Most engineering teams rely on line coverage to measure test quality. It’s the standard metric in CI pipelines. It’s easy to track. It’s widely understood.
But there’s a problem:
Line coverage tells you the percentage of lines containing executable code were executed—not whether your tests would catch a real bug.
Most engineering teams rely on line coverage to measure test quality. It’s the standard metric in CI pipelines. It’s easy to track. It’s widely understood.
But there’s a problem:
Line coverage tells you the percentage of lines containing executable code were executed—not whether your tests would catch a real bug.
Today, we’re launching Diffblue Test Quality Agent—a free tool that helps you understand how effective your tests actually are across Java and Python projects.
The gap most teams can’t see
If your test suite shows:
- 75–85% line coverage
- Healthy CI pipelines
- Passing builds
…it’s easy to assume your code is well tested.
But line coverage alone doesn’t tell you:
- Whether assertions are relevant and strong enough to catch regressions
- Whether the 15–25% uncovered lines are actually your most critical business logic
- Whether branching logic and error handling are adequately tested
- Whether your tests would fail if the code were subtly broken
In practice, many teams measure whether their tests execute code—but not whether the tests effectively protect it.
A better way to measure test quality
Diffblue Test Quality Agent gives you a clearer answer to a more important question:
If your code broke, would your tests catch it?
To answer that, it combines multiple signals into a single analysis:
- Line coverage → what your tests execute
- Branch coverage → how much logic they explore
- Mutation score → how effectively your tests detect defects
- Test strength → an overall measure of the real quality of your tests
The result is a far more meaningful view of test effectiveness than coverage alone.
The power of mutation testing
Mutation testing introduces small, controlled changes into your code and checks whether your tests fail.
If they don’t, that’s a gap.
For example, a mutation testing engine might:
- Change a conditional operator
- Modify a return value
- Invert a comparison
- Remove logic entirely
If your tests still pass, they may be executing the code—but they are not truly validating behaviour.
This is why mutation testing has become one of the most trusted indicators of regression protection in modern software engineering.
Java teams have historically relied on tools like PIT (often called PITEST), while Python developers frequently use tools like mutmut. These tools helped popularise mutation testing, but they can still be difficult to operationalise consistently across large engineering organisations.
Diffblue Test Quality Agent builds on these principles by making mutation testing easier to run, easier to interpret, and more actionable at the codebase level.
What you get in one run
Run the agent on your Java or Python project and you’ll receive a structured report showing:
- Line and branch coverage across your codebase
- Mutation score per class or module
- Test strength indicators
- Clear signals of where your tests are strong—and where they’re superficial
The result is a complete picture of your test suite, not just a surface-level metric.
What teams typically discover
Across real-world projects, the patterns are consistent:
- High coverage often hides weak tests
- Critical modules can have surprisingly low mutation scores
- Test quality varies significantly across the same codebase
- CI pipelines spend time running tests that provide little regression protection
- Strong tests exist—but not in enough of the right places
In other words:
“Green CI” doesn’t always mean “safe to ship.”
Built for real engineering workflows
Diffblue Test Quality Agent is designed to fit naturally into how teams already work:
- Works with Java and Python projects
- Supports modern engineering and CI/CD workflows
- No complex setup required
- Generates reports suitable for audits and engineering reviews
- Free to use, with no barrier to getting started
Whether you’re an individual developer exploring mutation testing for the first time or an enterprise engineering organisation evaluating test quality at scale, you can run a full assessment in minutes.
From insight to action
Once you can see where your tests fall short, the next step becomes obvious:
Improve them.
Teams use the output of Diffblue Test Quality Agent to:
- Prioritise high-risk areas
- Strengthen weak tests
- Reduce regression risk
- Improve deployment confidence
- Prepare for audits and compliance reviews
And for teams looking to move faster, it creates a natural path to automated test generation—helping close gaps without manual effort.
Try it on your codebase
If you’ve ever wondered whether your tests are giving you real confidence—or just good-looking coverage metrics—this is the easiest way to find out.
Run Diffblue Test Quality Agent on your Java or Python project and get a complete view of your test quality in minutes.
Run your free test quality report.
