7 ways to automatically increase test coverage in 2026 (tools compared)

Raising test coverage is the kind of work everyone agrees is worth doing and almost nobody wants to do. The good news is that 2026 has more options than ever for getting it done with AI. The bad news is that most of them stop at "here is a test" and leave the hard part, knowing whether the test is any good, to you.

Here are seven approaches, what each is genuinely good at, and where each one runs out of road. They are roughly ordered from most hands-on to most done-for-you.

1. Writing tests by hand

Still the baseline, and still the highest-quality option per test. You know the code, you know what should break, and you write the assertion that catches it. The problem is throughput: covering a backlog of untested modules by hand is slow, boring, and the first thing to get cut when a deadline shows up. Most teams that "mean to get to coverage" never do.

Good at: quality, intent, edge cases you actually care about. Falls short: speed, and the motivation to do it at all.

2. GitHub Copilot

Copilot will happily autocomplete a test as you type and, in chat, draft a test file for a function you paste in. It is fast and it is already in most editors. The catch is that it suggests, it does not verify. You still have to run the suite, check that coverage actually moved, and weed out tests that pass without asserting anything meaningful.

Good at: in-flow test drafting while you code. Falls short: it does not know or care what your coverage number is.

3. Cursor and other AI editors

AI-native editors like Cursor can generate whole test files from a prompt and iterate on them with you in the loop. With good prompting they get close. But the loop is still you: you run, you read the failures, you re-prompt. For one file that is fine. For a hundred, it is a second job.

Good at: generating tests interactively with a human steering. Falls short: it does not scale to a whole repo without a lot of your time.

4. Qodo (formerly Codium)

Qodo focuses specifically on test generation and offers a coverage-oriented mode that targets uncovered code. This is a real step up from generic autocomplete because the tool is reasoning about what is not covered yet. You still review and merge, and quality varies by codebase, but the intent is right.

Good at: test generation aimed at the coverage gap. Falls short: you own the review, the cleanup, and the merge.

5. Early and other unit-test generators

A class of tools now generates unit tests automatically from your functions and runtime behavior. They can produce a lot of tests quickly. The risk is the one everybody worries about with AI tests: volume over value. A hundred generated tests that touch lines without catching bugs inflate the number without improving the suite.

Good at: volume, quickly. Falls short: the tests need a careful human pass or they are just coverage theater.

6. Diffblue Cover

For JVM languages, Diffblue Cover autonomously writes unit tests and is genuinely strong in its lane. If you are on Java, it is worth a look. For JavaScript and TypeScript teams it does not apply, which is most of the web.

Good at: autonomous unit tests for Java. Falls short: not for JS/TS.

7. TaskBounty Coverage Uplift

This is the one we build, so read it with that in mind. TaskBounty Coverage Uplift is the done-for-you option: you point us at a JavaScript or TypeScript repo, we take it to 80% line coverage and hand you a pull request, and every test runs in an isolated sandbox against your real suite before the PR reaches you. It is a flat price, and if we miss the target you do not pay.

The difference from everything above is the verification and the outcome. The tools in this list hand you tests and trust you to check them. We make the check the product: coverage has to actually increase on the lines we claim, your existing tests have to stay green, and there is a quality bar that rules out mock-assertion spam and snapshot padding. You get a before-and-after report and you review the PR on your own timeline.

Good at: clearing a coverage backlog without spending your team's time, with the quality verified. Falls short: JavaScript and TypeScript only at launch, and it is a service, not a tool you run yourself.

How to choose

Covering code as you write it: Copilot or Cursor.
Targeted generation against the gap, with you reviewing: Qodo.
A pile of tests fast, with a careful review budget: Early-style generators.
Java: Diffblue.
A real coverage number raised without spending your team's time, verified before it ships: TaskBounty Coverage Uplift.

Whichever you pick, anchor on 80 percent rather than chasing 100, and measure your real number before you start. You can check any public repo for free, or run a read-only scan on a private one, and see exactly where your gap is before deciding how to close it.