Trends

The Trends page shows three time-series charts that reveal whether your codebase is getting healthier or accumulating debt. Use these charts to measure the impact of refactoring efforts, catch regressions early, and set data-driven sprint goals.

The Three Charts

1. Violations Over Time

A line chart showing the total number of active violations at each analysis point.

X axis: Time (each data point corresponds to an analysis run). Y axis: Violation count. Lines: One line per severity level (Critical, Warning, Info), each in its own color. Critical is red, Warning is amber, Info is blue.

How to read it:

• A downward trend means the team is actively fixing violations --- the codebase is improving.
• A flat line means violations are being introduced at the same rate they are resolved --- the team is treading water.
• An upward trend means new violations are outpacing fixes --- debt is accumulating.

The most important line is Critical. A rising critical violation count means more PRs are being blocked and developer velocity is suffering.

2. Debt Delta Per PR

A bar chart showing the debt delta score for each analyzed pull request.

X axis: Pull requests in chronological order (labeled by PR number). Y axis: Debt delta score. Bar color: Green for negative deltas (PR reduced debt), gray for zero or small positive deltas, red for deltas exceeding the gate threshold (default 15).

How to read it:

• Green bars mean that PR actively improved the codebase --- it removed more debt than it introduced.
• Gray bars mean the PR was neutral or introduced minor debt within acceptable limits.
• Red bars mean the PR was blocked (or would have been blocked) by the merge gate.

This chart is especially useful for identifying patterns: if the same module or the same type of change consistently produces red bars, it signals a systemic issue that needs architectural attention.

3. Complexity Trends

A line chart tracking average cyclomatic complexity across the project over time.

X axis: Time. Y axis: Average cyclomatic complexity per function. Line: A single line showing the rolling average, with a shaded band showing the min--max range.

How to read it:

• Increasing average complexity means functions are getting harder to understand and test.
• A widening min--max band means complexity is concentrated in a few files while others remain simple --- the hotspots are getting worse.
• Decreasing average complexity means refactoring efforts (splitting large functions, extracting helpers) are working.

Time Range Selectors

Each chart has a time range selector with the following options:

Range	Description
7 days	Last week. Useful for daily standups and quick checks.
30 days	Last month. Useful for sprint retrospectives.
90 days	Last quarter. Useful for quarterly planning and trend analysis.
All time	Full project history since the first analysis.

The selected time range applies to all three charts simultaneously.

Module Filtering

A module dropdown above the charts lets you filter data to a specific module. When a module is selected:

• Violations Over Time shows only violations within that module
• Debt Delta Per PR shows only the debt contribution from changes in that module
• Complexity Trends shows the average complexity of functions within that module

Select All modules to return to the project-wide view.

Tip: Use module filtering to compare the health of different parts of your codebase. If one module consistently shows worsening trends while others improve, it may need dedicated refactoring attention.

Using Trends for Sprint Planning

Setting Debt Reduction Targets

1. Open the Trends page and select the 30 day range
2. Note the current total violation count and the average debt delta per PR
3. Set a sprint goal: "Reduce critical violations from 12 to 8" or "No red bars in the debt delta chart this sprint"
4. At the end of the sprint, return to Trends and verify progress

Identifying Regression vs. Improvement

Compare two time ranges:

1. Select 30 days and note the violation trend direction
2. Select 90 days to see if the current trend is consistent with the longer-term trajectory

A codebase that shows improvement over 30 days but degradation over 90 days may be in a temporary improvement phase after a recent push --- the underlying trend is still negative.

Correlating with Releases

Debt delta spikes often correlate with feature releases. If you see a cluster of red bars in the debt delta chart, check the PR titles for that period. Major feature work sometimes introduces technical debt that needs immediate follow-up.

Data Availability

Trend data is available from the first analysis. Projects with fewer than 5 data points show the charts but with a notice that trends become more meaningful with more history.

Historical data is retained for the lifetime of your subscription. Downgrading or canceling does not delete historical trend data --- it remains accessible if you resubscribe.