JuliaStats/Statistics.jl erreicht einen Gesundheitsindex von 56 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Sustainability & Governance (77/100) ab, am schwächsten bei AI Readiness (27/100). Zuletzt vor 72 Tagen aktualisiert. 9 Mitwirkende tragen den Großteil der jüngsten Arbeit.
56
gesamt / 100
Mittel
Software-Gesundheitsindex
Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.
56
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
Bewertungsprofil
Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Release-Aktualität — letztes Release vor 950 Tagen
12.6/27
Release-Rhythmus — ein Release etwa alle 216,8 Tage
0/10
OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count
7
latest_release_tag
v1.11.1
releases_from_tags
nein
days_since_latest_release
950
mean_days_between_releases
216,8
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.
Typprüfbarer Code — Julia ohne Typprüfungs-Konfiguration
0/55
Handhabbare Dateigrößen — keine Quelldateien erkannt
Verwendete Eingangsdaten
primary_language
Julia
largest_source_bytes
—
source_files_sampled
0
oversized_source_files
0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Handhabbare Dateigrößen. Die verbleibenden Gewichte wurden renormalisiert.
Eckdaten
90GitHub-Sterne
87Mitwirkende
3Commits, letzte 12 Monate
72Tage seit letztem Push
7Releases
9Bus-Faktor
54offene Issues
—Paket-Ökosysteme
Warnungen zur Datenerhebung
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Weitere Details
Stern- und Fork-Verlauf 0 ★ / 50 ⇿
0Sterne
50Forks
6Releases
Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.
Major 0Minor 5Patch 1
Jeder Punkt umfasst 6 Tage.
OpenSSF Scorecard 4.8 / 10
4.8Gesamtwert
Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).Scorecard v5.5.0 · 2026-07-26 23:05 UTC
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 0 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
Registry
Paket
Version
Beziehung
Abhängigkeits-Advisories nicht bewertet
Der Advisory-Abgleich konnte für diesen Bericht nicht ausgeführt werden: No resolved dependencies to assess
JSON-Rohbericht maschinenlesbar
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"body": "The `a + γ*(b-a)` introduced by JuliaLang/julia#16572 has the advantage that it\r\nincreases with `γ` even when `a` and `b` are very close, but it has the drawback\r\nthat it is not robust to overflow. This is likely to happen in practice with\r\nsmall integer and floating point types.\r\n\r\nConversely, the \n[…]\nγ`. This can be problematic as it breaks an expected invariant.\r\n\r\nSo keep using the `a + γ*(b-a)` formula when `a ≈ b`, in which case it's almost\r\nlike returning either `a` or `b` but less arbitrary.",
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"body": "We do not care about the actual error code here, but as seen on some of\nthe other tests that needed similar fixes, these obstruct improvements\nto Base error messages.",
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"headline": "fix tests for error types",
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"body": "`std` has no `means` kwarg, the argument is always called `mean`, even\r\nif it contains several values. Since the next paragraph already explains\r\nthe use of mean together with dims, the wrong part can just be deleted.",
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"body": "* Restrict `middle(::AbstractRange)` eltype and improve performance\r\n\r\n* Revert eltype restriction\r\n\r\n* Apply suggestions from code review\r\n\r\nCo-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>\r\n\r\n* Fix typo: `r` -> `a`\r\n\r\n* Update test/runtests.jl\r\n\r\nCo-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>\r\n\r\n* Fix CI failure\r\n\r\n* Add `middle(0:typemax(Int))` test\r\n\r\nCo-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>",
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"oid": "cdd95fea3ce7bf31c68e01412548688fbd505903",
"body": "Use the same wording as for `sum`.",
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"headline": "Fix signature in `mean(f, ...)` docstring (#110)",
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"body": "`stdm` is missing a \"dims\" argument which is documented but has not actually been added.",
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"headline": "Fix missing `stdm` method with dims argument (#81)",
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"headline": "doc: fix code highlight language. (#97)",
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"headline": "adding docu to mean! explain target should not alias with the source",
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"body": "`dot` currently throws when the input contains `missing`,\r\nwhich is breaking as they were previously accepted.\r\nUse `adjoint(y) * x` instead of `dot(y, x)`, as the former falls back\r\nto the latter for arrays of `Number`s but to\r\n`sum(uu*vv for (uu, vv) in zip(u, v))` for other types.",
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