Runtime coverage · Session replay · Test impact

Know exactly what your tests really cover

CoverOps attaches lightweight agents to your running services and turns every functional test — automated or manual — into line-level coverage, a replayable session and a cross-service call tree.

One flag per service · first coverage in minutes · no code changes

runtimes — Java, Node.js, .NET
3
runtimes — Java, Node.js, .NET
runtime overhead
<1%
runtime overhead
of tests attributed to code
100%
of tests attributed to code
per session replay, not GBs
KBs
per session replay, not GBs

The parts people remember

Not a coverage report. A flight recorder for your test runs.

Replays cost KBs, not GBs

Session replay, down to the DOM

Every recorded test — automated or a tester clicking through — plays back pixel-for-pixel from a DOM recording that costs kilobytes, not video files. Console, network with request/response bodies, Web Vitals, DOM changes and backend hops sit on the same clock: click any row and the player seeks to that exact moment.

Debug mode: one step per Space

Re-run any scenario on the live app

One click packs a session's user steps into a link; opening it replays them on the running application — clicks, typing, navigation — while a live step list marks progress. Flip on debug mode and advance step by step with the space bar. The re-run records itself and carries the name of the person who launched it.

Annotated screenshot → Jira

Tester mode that files real bugs

The in-page widget records named sessions, replays catalogue cases, and captures the screen when something is wrong. Draw arrows, boxes and notes over the screenshot — the annotated capture lands in Jira as an attachment on the bug, with the session linked.

Dead code → runnable scenario

Call trees with coverage, per hop

Each session unfolds as a New-Relic-style trace: every service hop with the classes and methods that actually ran, framework plumbing folded away. Click a red block in any source file and CoverOps hands you the recorded scenario that exercises it.

What you actually see

Coverage on the code itself, not in a summary row

Every file opens like this: green ran, red never did, amber took one branch and not the other. Hover a line to see which tests executed it — and every red block offers the nearest recorded scenario that would reach it, one click to replay.

Who ran line 133

  • REG-006::Contract → Commission
  • property purchase smoke

Per-test attribution, across service hops: the platform knows which lines each Playwright, Cypress or manual session executed.

Changed-code gate, this branch

8.8%of the 61 changed lines are tested

One CLI call, exit 0/1/2, a commit status on the PR. The repository average stays flattering; this number tells the truth about today.

Platform

Coverage that answers questions, not just percentages

Agents for every runtime

Java (bytecode), Node.js (V8) and .NET (IL weaving) agents attach with one flag — no code changes, under 1% overhead. Parallel shards merge into a single run.

Per-test attribution

Every request carries its test's identity across service hops, so the platform knows which lines each Playwright, Cypress, Selenium or manual test actually executed.

Change-based test selection

Connect git, pick a date, and the diff is matched against what every test touched on its last run. Schedule only the impacted cases — minutes instead of hours.

Coverage monitoring

A regression that runs over days, mixing automation and manual testing? Turn monitoring on; every agent joins, resets and accumulates until you stop it.

A service map that is true

Built from recorded traces, not a diagram: which services requests walk through, in what order, and which methods run hottest — as APM-style cards you can zoom and pan.

Multi-project, multi-repo

A product can span many repositories and services — define projects, choose which services and repos each one watches, and share common ones between them.

Fits the tools you have

Playwright, Cypress, Selenium/JUnit 5, Postman, k6, GitHub Actions, Jenkins, GitLab CI, Kubernetes auto-attach — plus a plain REST API for everything else.

Jira, Xray & TestRail, both ways

Import cases into the catalogue, sync run verdicts back, and file tester bugs — with annotated screenshots attached — straight into your Jira project.

How it works

From first agent to change-based testing in an afternoon

  1. 01

    Attach the agents

    One JVM flag, one NODE_OPTIONS entry or one .NET startup hook per service — or a single Kubernetes annotation for the whole cluster.

  2. 02

    Run your tests

    Functional suites, UI automation, load tests, manual click-throughs. Each test names itself in a header; the agents do the rest.

  3. 03

    See what really ran

    Line-level coverage per service, per file and per test — with the gaps your suite never reaches called out explicitly.

  4. 04

    Run less, ship faster

    The next release only needs the tests its diff impacts. The platform picks them, schedules them and reports the verdicts.

Integrations

Plugs into the pipeline you already run

PlaywrightCypressSelenium / JUnit 5Postmank6GitHub ActionsJenkinsGitLab CIKubernetesJira / XrayTestRailZephyr Scale

Request a demo

See it on a system that looks like yours

Thirty minutes, your questions first. We will walk a multi-service demo — coverage per test, session replay, the changed-code gate — and map it to your stack. No slides unless you ask for them.

We use these details only to reply about the demo.

Stop guessing what your regression suite covers

Attach the first agent in minutes. The first run tells you what your tests really reach — and what they never have.

Get started