JuliaDebug/Debugger.jl erreicht einen Gesundheitsindex von 61 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Vitality (74/100) ab, am schwächsten bei AI Readiness (31/100). Zuletzt heute aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
61
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.
61
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-Rhythmus — ein Release etwa alle 143,2 Tage
0/10
OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count
34
latest_release_tag
v0.8.0
releases_from_tags
nein
days_since_latest_release
8
mean_days_between_releases
143,2
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
508GitHub-Sterne
27Mitwirkende
55Commits, letzte 12 Monate
0Tage seit letztem Push
34Releases
1Bus-Faktor
27offene 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 ★ / 47 ⇿
0Sterne
47Forks
25Releases
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 7Patch 18
Jeder Punkt umfasst 7 Tage.
OpenSSF Scorecard 5.2 / 10
5.2Gesamtwert
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 16:38 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": "An error thrown by code evaluated at the `|julia>` prompt printed twelve\nframes of machinery (eval_code, LineEdit, run_interface, RunDebugger, ...)\nbelow the actual error. `_eval_code` returned `Base.catch_stack()`, a\n`Vector{Any}` that `Base.scrub_repl_backtrace` deliberately ignores — and\nthe REPL\n[…]\n boundary (including nested `eval` in the evaluated code)\nare preserved.\n\nCo-Authored-By: Claude Fable 5 <noreply@anthropic.com>\nClaude-Session: https://claude.ai/code/session_01TUQRBLr8aoN2p1Q8BrLdzE",
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