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2 dépôts

Awesome GitHub RepositoriesAlgorithmic Efficiency Optimizers

Tools and metrics for refining code logic to improve performance and efficiency in algorithmic tasks.

Distinct from Performance and Optimization: Distinct from Performance and Optimization: focuses on code-level logic efficiency and scoring rather than general runtime or bundle optimization.

Explore 2 awesome GitHub repositories matching part of an awesome list · Algorithmic Efficiency Optimizers. Refine with filters or upvote what's useful.

Awesome Algorithmic Efficiency Optimizers GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • hyperjumptech/grule-rule-engineAvatar de hyperjumptech

    hyperjumptech/grule-rule-engine

    2,505Voir sur GitHub↗

    Grule is a business rule engine for Go that decouples complex decision-making logic from core application code. It provides a framework for defining, versioning, and executing business rules through a domain-specific language, allowing logic to be managed independently of the underlying software implementation. The engine distinguishes itself by utilizing a formal grammar-based parser and a Rete-inspired pattern matching algorithm to evaluate logic against data facts efficiently. It supports dynamic system modeling by enabling runtime updates to policies and providing thread-safe knowledge ba

    Applies cycle detection and algorithmic shortcuts to ensure fast and efficient rule evaluation.

    Gogolanghacktoberfesthacktoberfest2021
    Voir sur GitHub↗2,505
  • 0xax/go-algorithmsAvatar de 0xAX

    0xAX/go-algorithms

    1,949Voir sur GitHub↗

    This library provides a comprehensive collection of fundamental computer science primitives implemented in Go. It serves as a resource for both educational purposes and production applications, offering standard tools for organizing, searching, and sorting data. The implementation leverages language-level type parameters to ensure type safety while maintaining flexibility across different data types. It utilizes interface-driven polymorphism and pointer-based memory management to define common behaviors and handle complex structures. To optimize performance, the library employs in-place data

    Arranges unordered collections into specific sequences using standard algorithms to optimize data processing.

    Goalgorithmdata-structuresgo
    Voir sur GitHub↗1,949
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