harvard-edge/cs249r_book

Weekly average

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Derived only from GitHub GraphQL starredAt events after daily star totals are reconciled.

180 observed daily rows. Missing days are not fabricated.

Hotness formula

40% Hot today + 40% Hot this week + 20% Breakout.

40% Hot today: 68
40% Hot this week: 36
20% Breakout: 35
Stars gained: 1d: 43
Stars gained: 7d: 61
Stars gained: 14d: 449
Stars gained: 30d: 2542
Stars gained: 90d: 27503

Per-day formula: 0.40 × Hot today + 0.40 × Hot week + 0.20 × Breakout.

Same-day multiplier = stars 1d ÷ max(1, stars 7d ÷ 7)
Weekly multiplier = stars 7d ÷ max(1, stars 30d ÷ 30 × 7)
Fortnight multiplier = stars 14d ÷ max(1, stars 90d ÷ 90 × 14)
Hot today = clamp(70 × log-scale(stars 1d, 1000) + 30 × breakout-scale(same-day, 4))
Hot week = clamp(75 × log-scale(stars 7d, 5000) + 25 × breakout-scale(weekly, 3))
Breakout = clamp(35 × breakout-scale(same-day, 4) + 40 × breakout-scale(weekly, 3) + 25 × breakout-scale(fortnight, 2.5))

Date	Stars	Stars 1d	Stars 7d	Stars 14d	Stars 30d	Stars 90d	Same-day multiplier	Weekly multiplier	Fortnight multiplier	Hot today	Hot week	Breakout	Stored score

Weekly average

Full metrics details

Derived from the displayed continuity, closure, shipping, liveness, and support-burden components.

180 observed daily rows. Missing days are not fabricated.

Reliability formula

30% Continuity + 30% Closure + 20% Shipping + 10% Liveness + 10% Support burden.

30% Continuity: 79
30% Closure: 92
20% Shipping: 90
10% Liveness: 100
10% Support burden: 99

Per-day formula: 0.30 × Continuity + 0.30 × Closure + 0.20 × Shipping + 0.10 × Liveness + 0.10 × Support burden.

Continuity = 35% active ratio 90d + 20% active ratio 30d + 15% PR efficiency 90d + 10% PR efficiency 30d + 10% liveness + 10% observed-history coverage
Closure = 55% PR merge efficiency 90d + 45% issue close efficiency 90d
Shipping = 100 × (20% × release ratio 30d + 30% × release ratio 90d + 50% × release ratio 180d); ratios are releases ÷ 2, 6, and 12, capped at 1
Support burden = 100 − 2 × open issues per 1,000 stars
Liveness = 100 × exp(−pushed days ago ÷ 120)

Stars, issues, pull requests, and releases are daily observations. Pushed-days and license are repository snapshot-derived inputs and are not independent historical GitHub events.

Date	Issues opened	Issues closed	PRs opened	PRs merged	Releases	Stars	Open issues	Pushed days ago	Continuity	Closure	Shipping	Liveness	Support burden	License	Observed days	Missing days	Needs healing	Stored score

Continuity30% of headline79

Activity on 73 of 90 tracked days in the last 90 and 19 of 30 in the last 30.

Activity pulse

Closure30% of headline92

Merged 434 of 482 PRs opened and closed 34 of 37 issues opened over the last 90 tracked days — PR flow carries 55% of this component, issue flow 45%.

PRs merged (90d)PRs opened (90d)Issues closed (90d)Issues opened (90d)

Shipping20% of headline90

14 releases in the last 180 days, 6 in the last 90 and 2 in the last 30 — a steady cadence scores highest.

Releases

Liveness10% of headline100

Last push 1 days ago — freshness decays as pushes age (roughly halves every 83 days without a push).

Repository

Support burden10% of headline99

Open-issue load isn't tracked for this repo yet.

Open issues Stargazers

Adoption confidence100

Modeled — how confidently teams are adopting this repo. Stargazers

Maintenance quality91

Modeled from PR/issue responsiveness and upkeep signals. Activity pulse

Risk score3

Modeled — lower is better; adoption and continuity risk. Repository

Stays active (30d)81%

Modeled chance the repo stays active over 30 days. Activity pulse

Stays active (90d)89%

Modeled chance the repo stays active over 90 days. Activity pulse

Release rhythm (180d)100

Regularity of releases over the last 180 days. Releases

Maintainer bus risk (90d)21%

Modeled — lower is better; concentration of commits in few maintainers. Contributors graph

Weekly total

Full metrics details

GitHub API observation. Historical values render only when the source provides a real observation for that day.