Understanding code quality over time¶

This page explains the mental model behind the code quality analyzer: which static metrics it tracks per commit and how it aggregates them per tick. For configuration keys and the output schema, see the Quality reference.

What it measures¶

The code quality analyzer tracks complexity, Halstead metrics, comment quality, and cohesion across Git history. For each commit, it runs four static analyzers on UAST-parsed changed files and produces per-file quality metrics.

Per-file metrics¶

For each changed file in a commit, the analyzer computes:

Statistical aggregation¶

Per-tick statistics are computed from per-file arrays:

• Mean, median, P95, max for complexity and Halstead volume
• Sum for delivered bugs and Halstead volume
• Min for comment score and cohesion (worst-case tracking)
• Total files analyzed and functions counted

Architecture¶

The quality analyzer follows the TC/Aggregator pattern:

1. Consume phase: For each commit, Consume() runs four static analyzers (complexity, Halstead, comments, cohesion) on each changed file's UAST, returning per-file metrics as a TC{Data: *TickQuality}. The analyzer retains no per-commit state.
2. Aggregation phase: A quality.Aggregator collects TCs, merges TickQuality data by time bucket (tick), and produces TICK results.
3. Serialization phase: SerializeTICKs() converts aggregated TICKs into JSON, YAML, binary, or HTML plot output via ComputeAllMetrics().

This separation enables streaming output, budget-aware memory spilling, and decoupled aggregation.

See also¶

• Quality reference — configuration keys and output schema.
• Quick start — run history analysis.