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.
Repository
terminal
The new Windows Terminal and the original Windows console host, all in the same place!
Average Developer Performance (ETV)
Year-by-year Trend:+789%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 |
|---|---|---|---|
| c334f91 | Move PointerId, focus and in-bounds handling down into Interactivity (#20017) | Dustin L. Howett | maint |
| 14f4271 | Fix Korean IME arrow key inserting character at wrong position (#20039) | jason | waste |
| 3104c8f | Fix selection markers appearing on scroll (#20045) | Carlos Zamora | waste |
| 01f8a40 | conpty: remove accidental bool; use BOOL instead (#20035) | Dustin L. Howett | maint |
| 2870a70 | Reinstate the (apparently) load-bearing empty bracketed paste (#20037) | Dustin L. Howett | waste |
| ec939aa | Update 'restart connection' action to reset internal state (#19971) | Carlos Zamora | waste |
| be5dcf8 | Fix MSB4019 error in ConPTY nupkg (#20029) | gcrtnst | – |
| 4ce79d7 | Implement OSC 7 for setting the CWD (#20019) | Leonard Hecker | grow |
| 69e4590 | Add setting for customizable delimiter for file drag-and-drop (#19799) | Vallabh Mahajan | grow |
| a1a43a4 | Terminal receives focus on drag n drop (#20003) | Ethan Balakumar | grow |
Move PointerId, focus and in-bounds handling down into Interactivity (#20017)
Fix Korean IME arrow key inserting character at wrong position (#20039)
Fix selection markers appearing on scroll (#20045)
conpty: remove accidental bool; use BOOL instead (#20035)
Reinstate the (apparently) load-bearing empty bracketed paste (#20037)
Update 'restart connection' action to reset internal state (#19971)
Fix MSB4019 error in ConPTY nupkg (#20029)
Implement OSC 7 for setting the CWD (#20019)
Add setting for customizable delimiter for file drag-and-drop (#19799)
Terminal receives focus on drag n drop (#20003)
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.
Contributors ranked by total performance (ETV) from analyzed commits.
| # | |||||
|---|---|---|---|---|---|
| 1 | Leonard Hecker86 commits | 19.6 | 3 | 7.3 | 9.3 |
| 2 | Dustin L. Howett125 commits | 14.5 | 3 | 8.2 | 3.4 |
| 3 | Carlos Zamora69 commits | 13.7 | 6.4 | 2.7 | 4.6 |
| 4 | 1 14666831+consvc30 commits | 6.7 | 2.2 | 4.3 | 0.1 |
| 5 | P pankaj.d.bhoj12 commits | 3.1 | 2.7 | 0.2 | 0.2 |
| 6 | J j4_james8 commits | 1 | 0.2 | 0.1 | 0.7 |
| 7 | E e82.eric1 commits | 1 | 0.4 | 0.6 | 0 |
| 8 | E ekoschik1 commits | 0.4 | 0 | 0 | 0.4 |
| 9 | 2 2119212+jsoref1 commits | 0.4 | 0.1 | 0.3 | 0 |
| 10 | A ayman.bagabas1 commits | 0.4 | 0.2 | 0.1 | 0 |
| 11 | R ray1 commits | 0.3 | 0.3 | 0 | 0 |
| 12 | 1 1590066+geekjosh1 commits | 0.3 | 0.3 | 0 | 0 |
| 13 | A alabuzhev1 commits | 0.2 | 0.2 | 0 | 0 |
| 14 | S sagar.bhure3 commits | 0.2 | 0 | 0 | 0.2 |
| 15 | 2 22416789351 commits | 0.2 | 0 | 0 | 0.2 |
| 16 | 3 31830590+killerdevildog1 commits | 0.2 | 0 | 0 | 0.1 |
| 17 | A abutcher-gh1 commits | 0.2 | 0 | 0.2 | 0 |
| 18 | 7 74742695+eleadufresne2 commits | 0.1 | 0.1 | 0 | 0 |
| 19 | 7 71526180+paulinek132 commits | 0.1 | 0.1 | 0 | 0 |
| 20 | 2 27575106+eevan783 commits | 0.1 | 0 | 0.1 | 0 |
| 21 | M mdanishkhdev3 commits | 0.1 | 0.1 | 0.1 | 0 |
| 22 | 7 72227515+aliremu1 commits | 0.1 | 0.1 | 0 | 0 |
| 23 | 1 168367584+vallabh-15042 commits | 0.1 | 0 | 0 | 0.1 |
| 24 | 1 1168515+halldk1 commits | 0.1 | 0 | 0 | 0.1 |
| 25 | 1 141048767+angesie1 commits | 0.1 | 0 | 0 | 0.1 |
| 26 | D dmitryk1 commits | 0.1 | 0.1 | 0 | 0 |
| 27 | V vamsiikrishnaak3 commits | 0.1 | 0 | 0 | 0.1 |
| 28 | 1 141186389+kavishahaswani1 commits | 0.1 | 0 | 0 | 0.1 |
| 29 | J jadelaga2 commits | 0.1 | 0 | 0 | 0.1 |
| 30 | Niels Laute2 commits | 0.1 | 0 | 0.1 | 0 |
| 31 | A adalinesimonian1 commits | 0.1 | 0 | 0 | 0.1 |
| 32 | 7 70444390+set-t1 commits | 0.1 | 0 | 0 | 0.1 |
| 33 | 9 97347821+divinstance1 commits | 0.1 | 0 | 0 | 0.1 |
| 34 | A albinbabuvarghese201 commits | 0.1 | 0 | 0 | 0.1 |
| 35 | T teo1 commits | 0.1 | 0.1 | 0 | 0 |
| 36 | S szpeter2 commits | 0.1 | 0 | 0.1 | 0 |
| 37 | A abhishekgiri04051 commits | 0.1 | 0 | 0 | 0.1 |
| 38 | 3 34635265151 commits | 0.1 | 0 | 0 | 0.1 |
| 39 | Heiko1 commits | 0.1 | 0.1 | 0 | 0 |