awesome-repositories.com
Blog
awesome-repositories.com

Découvrez les meilleurs dépôts open-source grâce à notre recherche par IA.

ExplorerRecherches sélectionnéesAlternatives open sourceLogiciels auto-hébergésBlogPlan du site
ProjetÀ proposNotre méthodologiePresseServeur MCP
Mentions légalesConfidentialitéConditions d'utilisation
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

4 dépôts

Awesome GitHub RepositoriesBug Pattern Mining

Analyzing commit history and code changes to identify recurring bug signatures and anti-patterns.

Distinct from General Bug Detection: None of the candidates cover the systemic analysis of commit history to extract bug patterns; they focus on individual bug reports or CSS snippets.

Explore 4 awesome GitHub repositories matching software engineering & architecture · Bug Pattern Mining. Refine with filters or upvote what's useful.

Awesome Bug Pattern Mining GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • apache/cassandraAvatar de apache

    apache/cassandra

    9,778Voir sur GitHub↗

    Cassandra is a distributed NoSQL database and wide-column store designed for high availability and linear scalability. It functions as a fault-tolerant distributed system that utilizes an LSM-tree storage engine to optimize write throughput and manage massive datasets. The system is a CQL-compliant database, using a structured query language to manage and retrieve tabular data stored across multiple nodes. It organizes information into rows and columns based on a flexible schema and primary keys. The project provides capabilities for horizontal database scaling, distributed data partitioning

    Provides tools to scan commit history and summarize recurring bug patterns within the codebase.

    Javacassandradatabasejava
    Voir sur GitHub↗9,778
  • progit/progit2Avatar de progit

    progit/progit2

    6,522Voir sur GitHub↗

    Ce projet est une ressource éducative complète et un guide pour apprendre le système de contrôle de version Git. Il sert de source de documentation technique pour un manuel qui explique les fondamentaux, les workflows avancés et l'architecture interne de Git. Le projet est structuré comme un e-book multi-format, avec des fichiers sources conçus pour être compilés dans divers formats de publication numérique, incluant HTML, PDF, EPUB et Mobi. Il utilise un pipeline de build dédié pour générer et valider ces documents. Le contenu couvre un large éventail de capacités de contrôle de version, incluant la manipulation de l'historique, l'administration de dépôt et l'intégration système. Il fournit des instructions guidées sur la gestion des workflows—tels que le branching, le merging et le rebasing—et analyse la mécanique interne du système de fichiers adressable par contenu et le versioning basé sur des instantanés.

    Explains how to use binary search to identify the specific commit that introduced a regression.

    CSS
    Voir sur GitHub↗6,522
  • google/clusterfuzzAvatar de google

    google/clusterfuzz

    5,574Voir sur GitHub↗

    ClusterFuzz is an automated platform that runs coverage-guided fuzzers at scale to find security and stability bugs in software. It orchestrates libFuzzer and AFL++ across distributed clusters of worker bots, collecting coverage feedback to guide input mutation and discover crashes. The platform provides a web-based dashboard for configuring fuzzing jobs, monitoring progress, and inspecting crash reports, with role-based access control to restrict sensitive features. The system automates the full fuzzing lifecycle, from build pipeline integration and corpus management to crash triage and bug

    Identifies the exact commit range where a bug was introduced through binary search across revisions.

    Pythonfuzzingsecuritystability
    Voir sur GitHub↗5,574
  • apache/incubator-devlakeAvatar de apache

    apache/incubator-devlake

    2,940Voir sur GitHub↗

    DevLake is a DevOps data platform and analytics tool designed to orchestrate data pipelines that ingest, transform, and sync metadata from external development tools into a unified database. It functions as a system for collecting and normalizing data from source control, CI/CD pipelines, and issue trackers into a standardized schema to enable consistent software delivery analytics. The platform distinguishes itself by transforming tool-specific data into a common domain model, allowing for the calculation of engineering metrics via SQL. It provides specialized frameworks for measuring DORA m

    Provides visualizations of bug patterns and resolution timelines to analyze quality issues.

    Godashboard-friendlydatadata-analysis
    Voir sur GitHub↗2,940
  1. Home
  2. Software Engineering & Architecture
  3. Bug Pattern Mining

Explorer les sous-tags

  • Bug Introduction Range IdentifiersDetermines the commit range where a bug was first introduced through binary search across revisions. **Distinct from Bug Pattern Mining:** Distinct from Bug Pattern Mining: focuses on identifying the introduction range of a specific bug, not mining patterns from commit history.
  • Trend VisualizationsVisual representations of recurring bug patterns and resolution timelines over time. **Distinct from Bug Pattern Mining:** Focuses on the visualization and temporal analysis of trends rather than the act of mining the patterns from code.