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Passing unit tests do not necessarily collect coverage. A 0% result usually means either the coverage tool never measured the intended code, or a valid report was not generated, transferred, or matched to the source files being analyzed. First inspect the report created by the test job: if it is also 0%, troubleshoot collection and instrumentation; if it shows coverage, troubleshoot the analysis and CI handoff.
Trace the coverage pipeline from tests to dashboard
A coverage result depends on several separate steps. Tests can pass while any later step fails:
- Tests run against the intended code.
- A coverage collector instruments or observes that code.
- The collector writes raw coverage data.
- A report is generated in a format the analyzer accepts.
- The report reaches the analysis job and is read from the configured path.
- The analyzer matches report paths to the source files it analyzes, and the dashboard displays the intended metric and commit.
Coverage measures which code ran under a coverage tool; it is not the same as test pass/fail status. Coverage.py, for example, documents running code under coverage separately from reporting the measurements and producing formats such as XML and LCOV: Coverage.py documentation.
Start by checking the report, not changing settings at random
- Reproduce the CI test command. Record the exact command, working directory, environment, build variant, and revision where possible.
- Look for coverage-specific output. A test summary such as JUnit or TRX confirms test results, not coverage. If there is no coverage summary or raw data file, check that the collector is installed and enabled in the command or runner.
- Locate newly generated files. List files immediately after the tests. Confirm that the report is recent and nonempty instead of assuming its default location.
- Open the report or render a human-readable one. Check that it parses, includes the expected application files, and has meaningful line or statement totals. A report containing only test files is not evidence that the production code was measured.
- Compare local coverage with the analysis result. If the report itself is empty or zero, focus on collection, instrumentation, scope, or filters. If it has expected coverage, focus on format, configured path, job transfer, source-path matching, and revision.
- Read analysis logs. Look for missing, unreadable, unsupported, or unmatched report messages. Use the analyzer’s verbose or debug option if available.
- Rerun analysis for the same commit. Confirm that the correct branch and coverage metric changed after the fix.
If the generated report is zero or missing
Confirm that the test run actually enables a collector
Many test runners do not collect coverage unless a plugin, agent, flag, or configuration setting enables it. Verify the exact CI command and that instrumentation applies to the application code, not just the tests. A test passing only establishes that its assertions passed; it does not prove that a coverage tool measured the intended production files.
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Check scope, filters, and the tested target
Inspect collector include/omit patterns, package and module selection, analyzer exclusions, and source-root settings. Also verify that the tests exercised the same assembly, package, build output, or source revision the analysis examines. Tests can pass against an installed dependency or stale build while the analyzer scans a different checkout.
Account for subprocesses, shards, and modules
Coverage data may be split across child processes, parallel workers, test shards, modules, or machines. Ensure the collector measures relevant processes, combines their data where required, and generates the report from the combined result rather than one partial worker. Coverage.py documents subprocess and multiprocessing setup, parallel data files, and combining measurements: Coverage.py process measurement and Coverage.py run command.
If the report has coverage but static analysis shows 0%
Use a supported report format and the actual path
Raw profiler data, HTML, JaCoCo XML, Cobertura XML, and LCOV are different outputs. Check the analyzer’s current documentation for supported formats and configure the exact generated report path. For example, GitHub’s repository coverage upload instructions require Cobertura XML, while GitLab’s diff visualization accepts Cobertura or JaCoCo XML; these requirements are specific to those features, not universal analyzer rules. See GitHub code coverage setup and GitLab coverage report artifacts.
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Verify the report survives the CI job boundary
When tests and analysis run in different jobs or containers, the report must be uploaded and made available to the consumer job. Check job ordering, artifact paths, cleanup steps, and working directories. A report present in a test job is not automatically present in a separate analysis job.
Match report file names to the analyzed checkout
Compare the file paths recorded in the report with the analysis workspace. Absolute paths from another container root, module-relative paths, case differences, generated-source paths, or a different checkout layout can prevent a match. Where the tools support it, generate and analyze from the same revision and use stable relative paths or configure the correct source-root mapping.
Check branch, commit, and metric
Confirm the analysis uses the intended branch and commit SHA. Also distinguish total project coverage from changed-line or patch coverage: a CI feature may display a percentage parsed from logs, imported report data, or line annotations through separate mechanisms. GitLab documents percentage extraction separately from XML report artifacts and diff annotations: GitLab coverage reporting and GitLab coverage report artifacts.
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Language-specific checks and example commands
These are starting points from the respective tool documentation, not universal commands. Adapt package names, versions, paths, and report settings to the project and the consuming analyzer.
Python with pytest-cov
A common command that runs tests and emits terminal and XML reports is:
pytest --cov=your_package --cov-report=term --cov-report=xmlReplace your_package with the actual import package or source scope. Coverage.py’s XML command reads .coverage by default and writes coverage.xml; options include a different data file, output path, include/omit patterns, and configuration file. Its documentation notes that [run] include rather than [run] source can preserve complete file paths in XML, which may help path matching: Coverage.py XML command.
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JaCoCo separates agent-based collection from report generation. Check that the test phase runs with the JaCoCo agent and that the XML report goal runs before analysis. Maven Surefire or Failsafe configured with forkCount=0 or forkMode=never prevents tests from running with the configured JaCoCo Java agent. If Surefire uses a custom argLine, preserve the injected JaCoCo argument; JaCoCo documents late property evaluation such as @{argLine}. The commonly used Maven report location target/site/jacoco/index.html is HTML, so do not assume it means an XML report exists or that analysis imports it. See the JaCoCo Maven plugin and JaCoCo prepare-agent goal.
Java with Gradle and JaCoCo
Applying the Gradle JaCoCo plugin with the Java plugin creates a jacocoTestReport task. Its documented default HTML location is build/reports/jacoco/test; check the task’s XML setting and enable XML if the importing tool needs it. Run the report task after tests and verify the actual XML path before analysis: Gradle JaCoCo plugin.
.NET with VSTest
For VSTest-based workflows, Microsoft documents this command when the Coverlet collector is installed:
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dotnet test --collect:"XPlat Code Coverage"It produces coverage.cobertura.xml beneath TestResults, often inside a generated run-ID directory. Locate the file rather than hard-coding an assumed directory. Microsoft’s built-in collector uses the different friendly name "Code Coverage" and has different output format and location; do not give an importer a binary format when it expects Cobertura XML. See the Microsoft .NET code coverage guide and dotnet test options.
JavaScript or TypeScript with Jest
Jest’s collectCoverage setting defaults to false, so enable it with --coverage or configuration. Review collectCoverageFrom and coveragePathIgnorePatterns for patterns that miss or exclude the intended files. If coverageReporters is customized, it replaces the defaults; ensure the required output, such as LCOV, remains listed. See Jest configuration.
Go
For package unit tests, the Go tool documents:
go test -coverprofile=coverage.out ./...
go tool cover -func=coverage.outThe first command writes the profile and the second reports from it. Check that package selection matches the code the analysis expects. For application or integration tests using coverage-instrumented binaries, Go 1.20 introduced go build -cover and GOCOVERDIR; if GOCOVERDIR is unset, the program can run without emitting coverage data. See Go coverage profiling documentation.
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| What you observe | Likely area | What to verify |
|---|---|---|
| Tests pass; no raw data or report exists | Collector not enabled, installed, or attached | Test command, plugin or package, instrumentation, and generated files |
| Raw data exists; report is missing | Report-generation step omitted or reading different data | Report command/task, dependencies, working directory, and input file |
| Local report is also 0% | Code under test is not being measured, or scope is filtered | Instrumentation, target, include/exclude rules, and child-process coverage |
| Local report is nonzero; analysis is 0% | Import, format, path, transfer, or revision mismatch | Supported format, configured path, CI artifact handoff, source paths, and commit |
| Some modules or files have coverage; others do not | Partial aggregation or filters | Per-module reports, shard merging, source roots, and include/exclude rules |
| Report has rows but omits expected application files | Wrong scope or file mapping | Production-code filters, generated code, path prefixes, and checkout layout |
| Dashboard remains at 0% after a fix | Stale run, wrong branch or commit, or different metric | Analysis logs, run SHA, branch, and project-versus-patch coverage |
| Works locally but not in CI | Environment, process, workspace, or pipeline difference | Exact command, runtime, containers, parallel jobs, and artifact paths |
| Integration-tested code is missing | Separate runner or collector not included | Whether integration tests run with instrumentation and their data is merged |
Verify the fix in the pipeline
- The intended tests run with the coverage collector enabled.
- Fresh raw data and a supported report are created, and the report lists expected application files with nonzero coverage where appropriate.
- Parallel or subprocess results are merged before report generation when required.
- The analysis job receives the same report that the test job generated, at the configured path.
- Report paths correspond to the source checkout and revision being analyzed.
- Analysis logs show the report was read and matched, and the dashboard is displaying the intended branch, commit, and metric.
Do not make the percentage appear by excluding all source files: that hides the symptom without establishing a trustworthy measurement.
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