Files with the highest combination of change frequency and waste ratio. These are candidates for refactoring or closer review.
Cumulative contribution over time. Watch developers race as positions shift month by month.
Commit activity distribution by hour and day of week across all contributors in this repository.
Performance has many faces. Navigara breaks down the effort to visualize what parts of codebase has been changed and where energy flowed. Our Architect AI can break the performance even further into particular components and patterns.
Breakdown of file changes over time. Play the timeline to see how change types evolved across periods.
Monthly overview of bugs introduced and fixed, based on symbol-level commit analysis. Fixes show whether the original author fixed their own bug (self-fix) or someone else did (cross-fix).
Bug attribution uses symbol-level matching from commit history. For each fix commit, we look at the changed symbols (functions, classes, methods) and trace backwards to find who last modified that symbol in a non-fix commit. This person is the probable bug introducer. The algorithm only works when commits have symbol-level data from the Navigara analysis engine — the coverage rate shows what percentage of fix commits had this data available.
The current metrics model has a semantic inversion: when developer A creates a feature with a bug, they receive grow (positive). When developer B fixes that bug, they receive waste (negative). The bug creator is rewarded while the fixer is penalized. Bug attribution addresses this by explicitly tracking who introduced bugs and who fixed them, providing a more accurate picture of code quality contributions.
Currently computed client-side from commit data. Ideal server-side endpoint:
POST /v1/repositories/{repositoryId}/bug-attributions
Content-Type: application/json
Request:
{
"startTime": "2025-01-01T00:00:00Z",
"endTime": "2025-12-31T23:59:59Z"
}
Response:
{
"totalBugsAttributed": 42,
"selfFixRate": 35,
"coverageRate": 78,
"attributions": [
{
"filePath": "src/lib/auth.ts",
"symbol": "validateToken",
"introducer": { "name": "Alice", "email": "alice@co.com", "commitSha": "abc123" },
"fixer": { "name": "Bob", "email": "bob@co.com", "commitSha": "def456" },
"fixedAt": "2025-06-15T10:30:00Z",
"isSelfFix": false
}
]
}Reclassifies engineering effort based on bug attribution. Commits that introduced bugs are retrospectively counted as poor investments.
Investment Quality reclassifies engineering effort based on bug attribution data. Commits identified as buggy origins (those that introduced bugs later fixed by someone) have their grow and maintenance time moved into the Wasted Time category. Their waste (fix commits) remains counted as productive. All other commits retain their standard classification: grow is productive, maintenance is maintenance, and waste (fixes) is productive.
The standard model classifies commits as Growth, Maintenance, or Fixes. Investment Quality adds a quality lens: a commit that introduced a bug is retrospectively counted as a poor investment — the engineering time spent on it was wasted because it ultimately required additional fix work. Fix commits (Fixes in the standard model) are reframed as productive, because fixing bugs is valuable work.
Currently computed client-side from commit and bug attribution data. Ideal server-side endpoint:
POST /v1/organizations/{orgId}/investment-quality
Content-Type: application/json
Request:
{
"startTime": "2025-01-01T00:00:00Z",
"endTime": "2025-12-31T23:59:59Z",
"bucketSize": "BUCKET_SIZE_MONTH",
"groupBy": ["repository_id" | "deliverer_email"]
}
Response:
{
"productivePct": 74,
"maintenancePct": 18,
"wastedPct": 8,
"buckets": [
{
"bucketStart": "2025-01-01T00:00:00Z",
"productive": 4.2,
"maintenance": 1.8,
"wasted": 0.6
}
]
}Latest analyzed commits in this repository.
| Hash | Message | Author | Effort |
|---|---|---|---|
| eed1e9c | Add MaybeExternal helper to load config values from external sources | Leo Blöcher | grow |
| e0f15e8 | Add Settings/RawSettings wrappers to protect sensitive values | Leo Blöcher | grow |
| 36531c4 | Add ratelimit feature to library docs | Leo Blöcher | maint |
| f9fb7ec | Use StaticQuantaClock in telemetry rate limiters | Leo Blöcher | maint |
| 1c6e10d | Replace governor's default clock with StaticQuantaClock | Leo Blöcher | maint |
| 576dddc | Replace serde-yaml with serde-saphyr (#181) | takashialpha | maint |
| 85d0c8c | Add configurable rate limiting for sentry events | Leo Blöcher | grow |
| ce6a5fb | Add special `ratelimit=` syntax to logging macros | Leo Blöcher | grow |
| 25abc22 | Add ratelimit! utility macro | Leo Blöcher | grow |
| 08ea40a | Refactor slog::Drain setup code and fix rate limiting bug | Leo Blöcher | maint |
Add MaybeExternal helper to load config values from external sources
Add Settings/RawSettings wrappers to protect sensitive values
Add ratelimit feature to library docs
Use StaticQuantaClock in telemetry rate limiters
Replace governor's default clock with StaticQuantaClock
Replace serde-yaml with serde-saphyr (#181)
Add configurable rate limiting for sentry events
Add special `ratelimit=` syntax to logging macros
Add ratelimit! utility macro
Refactor slog::Drain setup code and fix rate limiting bug
Average context complexity and engagement score of file changes over time. Higher complexity means more intricate changes; higher impact means broader effect on the codebase.
Repository
foundations
Cloudflare's Rust service foundations library.
Average Developer Performance (ETV)
Year-by-year Trend:+74%Contributors ranked by total performance (ETV) from analyzed commits.
| # | |||||
|---|---|---|---|---|---|
| 1 | Leo Blöcher46 commits | 4 | 1.5 | 1.6 | 0.9 |