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AI for Jenkins Difficulty: Intermediate ClaudeChatGPT

Jenkins Test Reporting & Quality Gates Prompt

Publish test, coverage, and static-analysis results in Jenkins and enforce quality gates — JUnit/coverage trends, thresholds that fail the build, and warnings-as-errors — so quality regressions can't merge silently.

Target user
Engineers adding quality gates to a Jenkins pipeline
Difficulty
Intermediate
Tools
Claude, ChatGPT

The prompt

You are a CI engineer who makes test and quality results visible in Jenkins and turns them into gates that actually block bad changes.

I will provide:
- My test framework and report format (JUnit XML, coverage report, SonarQube, lint output)
- What quality bars matter (min coverage, zero new criticals, no new warnings)
- My pipeline and whether PR builds should gate merges

Your job:

1. **Publish results** — add steps to record test results (`junit`), coverage (Coverage plugin), and static-analysis warnings (Warnings NG / `recordIssues`) so trends and per-build detail show in the UI.

2. **Set gates** — define thresholds that fail or mark the build unstable: min coverage (or no-drop-from-baseline), no new critical issues, quality-gate status from SonarQube (`waitForQualityGate`). Prefer "no new regressions" over absolute numbers on legacy code.

3. **Fail correctly** — ensure a failed gate actually changes the build result (not just prints a warning), and that flaky-test noise is handled (retry/quarantine, not blanket ignore).

4. **PR gating** — surface the status back to the PR/MR so a failing gate blocks merge, and keep the message actionable (which check failed, by how much).

5. **Trends & baselines** — track coverage/warnings over time and use reference-build comparison so only new problems fail a PR.

6. **Reporting** — link the published reports in notifications so people can jump straight to the failure.

Output: (a) the publish steps for tests/coverage/analysis, (b) the gate thresholds + how they set build result, (c) the PR-gating wiring, (d) the flaky-test handling policy.

Bias toward: no-new-regression gates, results that truly fail the build, and disciplined flaky-test handling.

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