Interactive Demo

Explore the ContextQA Reporting & Analytics dashboard — track pass rates, detect flaky tests, classify failures by root cause, and share results with stakeholders.

The ContextQA analytics dashboard gives teams a real-time view of test health across every execution. This demo walks through the key panels: KPI summary, daily pass rate trends, AI failure classification, and flaky test detection.

Last 7 Days

1

KPI Summary

The top row shows the four most important health metrics for the selected time period at a glance.

Metric	Value	Trend
Pass Rate	94.2%	↑ 2.1% vs last week
Total Executions	847	↑ 18% vs last week
Failures	49	↓ 12 fewer than last week
Flaky Tests	7	↑ 2 new this week

AI Agent: KPIs update in real time after every execution. Pass rate, failure count, and flaky test count are all computed automatically — no manual tagging required.

2

Daily Pass Rate Chart

The bar chart shows passed, failed, and self-healed test counts for each day in the period.

7-day breakdown (passed / failed / healed):

• Monday: 98 / 5 / 2

• Tuesday: 112 / 8 / 3

• Wednesday: 89 / 12 / 1

• Thursday: 134 / 6 / 4

• Friday: 156 / 9 / 2

• Saturday: 78 / 3 / 1

• Sunday: 180 / 6 / 2

AI Agent: "Healed" counts are tests that failed on first attempt but passed after self-healing — these are tracked separately from clean passes so teams can monitor UI churn over time.

3

AI Failure Classification

Every failure is automatically classified by the AI into one of four categories — no engineer investigation needed to triage.

Classification	Count	Share
Application Bug	25	51%
Flaky Failure	14	29%
Test Bug	7	14%
Environment Issue	3	6%

AI Agent: AI classifies failures based on error type, console logs, and network traces. Application bugs are real regressions that need developer attention; flaky failures are retry-passed runs that need stabilization; test bugs indicate the test steps themselves need updating.

4

Flaky Test Detection ✓

ContextQA identifies tests that pass inconsistently across runs and surfaces them in a dedicated list with their flakiness rate and likely cause.

Top flaky tests this week:

Test	Flakiness	Likely Cause
Checkout — credit card payment	30%	Timing issue
Search — autocomplete results	20%	Race condition
Upload — large file (>10MB)	10%	Timeout
Email notification delivery	10%	Async timing

AI Agent: Flaky tests are flagged automatically based on pass/fail variance across recent runs. Teams can prioritize stabilization work based on flakiness rate without manually comparing run histories.

Filter options available: Last 7 days · Last 30 days · Last 90 days · Current Sprint

Capability	Detail
Failure Classification	Automatic — no manual tagging
Flaky Test Detection	Based on run variance across history
Shareable Reports	One-click export or shareable link
Stakeholder View	Summary dashboard with no login required

30 Days

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