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13 repository-uri

Awesome GitHub RepositoriesCode Correctness Verifications

Verifying code correctness by running generated completions against predefined test suites with parallel execution.

Distinct from Test Suite Execution: Distinct from Test Suite Execution: specifically targets code correctness verification of generated code, not general test suite execution.

Explore 13 awesome GitHub repositories matching testing & quality assurance · Code Correctness Verifications. Refine with filters or upvote what's useful.

Awesome Code Correctness Verifications GitHub Repositories

Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
  • applenob/cpp_primer_practiceAvatar applenob

    applenob/Cpp_Primer_Practice

    8,719Vezi pe GitHub↗

    This repository is a C++ study collection and programming courseware designed to support a structured language curriculum. It functions as a comprehensive study repository containing conceptual notes and verified exercise solution sets for learning the C++ programming language. The project provides a set of working source code implementations and answers for practical programming problems. These materials enable language learning and programming practice by allowing users to implement code and verify their logic against solved exercises. The content is organized into a chapter-based director

    Allows learners to verify the correctness of their programming logic by comparing implementations against solved answers.

    C++
    Vezi pe GitHub↗8,719
  • mingchaozhu/deeplearningAvatar MingchaoZhu

    MingchaoZhu/DeepLearning

    7,679Vezi pe GitHub↗

    This project is a deep learning implementation library and neural network theory repository. It translates mathematical derivations from textbooks and literature into functional Python code to demonstrate how deep learning algorithms work. The codebase focuses on low-level algorithm implementation by using numerical libraries instead of high-level deep learning frameworks. This approach maps theoretical mathematical proofs to executable functions to verify principles and expose the underlying arithmetic and data flow of neural networks. The project covers the implementation of deep learning

    Uses functional code implementations to verify the correctness of theoretical mathematical derivations.

    Pythonbayesiandeep-learningensemble-learning
    Vezi pe GitHub↗7,679
  • openxiangshan/xiangshanAvatar OpenXiangShan

    OpenXiangShan/XiangShan

    7,081Vezi pe GitHub↗

    XiangShan is a high-performance RISC-V processor core and a hardware description language framework. It provides a construction-based system for designing, simulating, and verifying complex processor micro-architectures and peripheral devices. The project includes a high-performance CPU simulator used for architectural exploration and functional verification of processor execution. The project implements a superscalar out-of-order CPU architecture that uses renaming and reorder buffers to execute instructions in parallel. It generates synthesizable Verilog files from hardware descriptions to

    Verifies processor core correctness by simulating binary workloads in a software environment before manufacturing.

    Scalachiselmicroarchitecturerisc-v
    Vezi pe GitHub↗7,081
  • reactivex/rxpyAvatar ReactiveX

    ReactiveX/RxPY

    5,014Vezi pe GitHub↗

    RxPY este o bibliotecă de programare reactivă funcțională și o bibliotecă de tip ReactiveX observable pentru Python. Acesta servește drept procesor de fluxuri asincrone și framework de coordonare bazat pe evenimente, utilizat pentru a construi pipeline-uri de date care reacționează la schimbările de stare sau la fluxurile de evenimente în timp. Biblioteca oferă un set de instrumente pentru compunerea programelor asincrone și bazate pe evenimente folosind secvențe observabile și operatori. Se distinge prin utilizarea de schedulere configurabile pentru a gestiona concurența, sincronizarea și ciclurile de viață ale abonamentelor. Proiectul acoperă o gamă largă de capabilități de procesare a fluxurilor, inclusiv agregarea, filtrarea și combinarea datelor. Oferă mecanisme pentru difuzarea evenimentelor, buffering-ul secvențelor și gestionarea erorilor, precum și instrumente pentru coordonarea fluxurilor observabile cu bucle de evenimente asincrone. Testarea și asigurarea calității sunt susținute prin simularea timpului virtual, modelarea cu diagrame marble și verificarea emisiilor.

    Allows capturing notifications from observables to assert correct value emissions at expected virtual timestamps.

    Python
    Vezi pe GitHub↗5,014
  • cheatsnake/backend-cheatsAvatar cheatsnake

    cheatsnake/backend-cheats

    4,619Vezi pe GitHub↗

    backend-cheats is a comprehensive backend engineering reference guide and a collection of technical cheatsheets. It serves as a knowledge base for server-side development, networking, and computer science fundamentals, delivered as a markdown-based static site. The project provides detailed handbooks for API design, specifically covering REST and GraphQL interfaces, and software architecture patterns such as Monolithic, Microservices, and MVC. It includes a database architecture overview comparing relational and NoSQL paradigms, as well as a web security reference for identifying vulnerabilit

    Details methods for verifying code correctness through the execution of diverse test suites.

    architectural-patternsarchitectureawesome
    Vezi pe GitHub↗4,619
  • erikbjare/gptmeAvatar ErikBjare

    ErikBjare/gptme

    4,334Vezi pe GitHub↗

    gptme este o platformă de orchestrare multi-agent concepută pentru inginerie software autonomă, integrare AI bazată pe terminal și navigare în cod îmbunătățită prin RAG. Permite implementarea agenților persistenți și a subagenților specializați pentru a descompune sarcini complexe și a executa fluxuri de lucru tehnice paralele. Sistemul se distinge printr-o combinație de automatizare GUI bazată pe viziune pentru controlul aplicațiilor desktop și mecanisme de patching chirurgical pentru modificări țintite ale codului sursă. Utilizează gestionarea memoriei bazată pe git pentru a menține un istoric versionat al identităților agenților, lecțiilor învățate și stărilor spațiului de lucru. Capabilitățile sale mai largi acoperă rutarea modelelor agnostice față de furnizor pe backend-uri AI locale și cloud, regăsirea semantică pentru context local și integrarea Model Context Protocol pentru a încărca dinamic instrumente externe. Proiectul include, de asemenea, o suită cuprinzătoare de inginerie software pentru debugging automat, refactoring și gestionarea repository-urilor GitHub. Platforma poate fi implementată ca un server self-hosted prin containere Docker, având o interfață de chat bazată pe web și randare desktop containerizată.

    Executes test suites after code modifications and automatically applies fixes to any resulting failures.

    Python
    Vezi pe GitHub↗4,334
  • openai/simple-evalsAvatar openai

    openai/simple-evals

    4,354Vezi pe GitHub↗

    This project is a language model evaluation framework and benchmarking tool designed to measure the accuracy and performance of models across diverse datasets. It provides a system for implementing model-based graders, running standardized tests for mathematical reasoning, coding, and factuality, and calculating quantified performance metrics such as precision, recall, F1 scores, and pass-at-k. The framework utilizes model-based grading and rubrics to validate response quality against expert-defined criteria. It includes a multi-model benchmarking loop and a model-agnostic API interface to co

    Verifies code correctness by running generated completions against predefined test suites with parallel execution.

    Python
    Vezi pe GitHub↗4,354
  • allendowney/thinkstats2Avatar AllenDowney

    AllenDowney/ThinkStats2

    4,212Vezi pe GitHub↗

    ThinkStats2 este un curs de statistică computațională și o bibliotecă educațională concepută pentru a preda probabilitatea și statistica printr-o abordare programatică. Oferă un framework pentru studierea conceptelor statistice prin scrierea de cod Python și rularea simulărilor pe seturi de date din lumea reală. Proiectul utilizează notebook-uri interactive și o colecție de module Python pentru a livra lecții ghidate. Pune accent pe verificarea legilor statistice teoretice prin experimente computaționale iterative și testare bazată pe simulare. Resursa acoperă capabilități largi în analiza datelor și formarea în știința datelor, permițând utilizatorilor să exploreze seturi de date și să efectueze analize statistice într-un mediu programabil.

    Uses repeated computational experiments to verify that empirical data aligns with theoretical statistical laws.

    Jupyter Notebook
    Vezi pe GitHub↗4,212
  • yosyshq/picorv32Avatar YosysHQ

    YosysHQ/picorv32

    4,222Vezi pe GitHub↗

    picorv32 is a size-optimized RISC-V CPU core and synthesizable processor IP designed for integration into FPGA and ASIC hardware designs. It serves as an open-source CPU architecture and embedded system-on-chip component that implements a standard RISC-V instruction set. The design features a modular architecture that allows for the integration of external coprocessors to implement custom non-branching instructions. It includes a parameterized integer unit with configurable multiplication and division cores to balance performance against total logic gate count. The project covers a broad ran

    Runs testbenches and firmware checks through simulators to ensure the processor core behaves correctly.

    Verilog
    Vezi pe GitHub↗4,222
  • enjoy-digital/litexAvatar enjoy-digital

    enjoy-digital/litex

    3,963Vezi pe GitHub↗

    LiteX is an FPGA SoC development suite and SoC builder framework used to programmatically design system-on-chips. It provides a hardware description toolchain that uses a scriptable framework to define hardware layouts and automate the generation of hardware description language code. The project distinguishes itself by orchestrating multiple vendor and open-source toolchains to synthesize digital logic and generate deployable bitstreams. It supports multi-language logic integration, allowing disparate hardware description languages to be combined into a single project. The framework covers

    Verifies the functional correctness of individual hardware blocks and communication protocols using simulators.

    Pythonfpgahardwaresystem-on-chip
    Vezi pe GitHub↗3,963
  • chipsalliance/rocket-chipAvatar chipsalliance

    chipsalliance/rocket-chip

    3,798Vezi pe GitHub↗

    Rocket-chip is a framework for the parametric design, synthesis, and verification of RISC-V based processors and system-on-chip hardware. It functions as a generator that converts high-level specifications into synthesizable Verilog files for FPGA or ASIC implementation. The project utilizes a Scala-based hardware description framework to produce customizable pipelined processor cores, memory hierarchies, and peripheral devices. It employs a parameter-driven model and a two-phase negotiation process to resolve hardware interface specifications between modules during the elaboration phase. Th

    Includes a verification suite using randomized testbenches to ensure architectural compliance of processor cores.

    Scalachip-generatorchiselriscv
    Vezi pe GitHub↗3,798
  • verilator/verilatorAvatar verilator

    verilator/verilator

    3,365Vezi pe GitHub↗

    Verilator is a hardware simulation engine and toolchain that translates Verilog and SystemVerilog hardware description languages into optimized C++ or SystemC models. It functions as a compiler and transpiler, converting hardware designs into executable binaries to achieve high-speed simulation and integration into software environments. The project distinguishes itself by focusing on simulation acceleration through the generation of optimized C++ classes and cycle-accurate models. It provides a SystemVerilog linter for static analysis of hardware designs and a hardware coverage analyzer to t

    Implements a verification workflow that collects code and functional coverage data to ensure design exercise.

    SystemVerilogcompilerscpprtl
    Vezi pe GitHub↗3,365
  • ghdl/ghdlAvatar ghdl

    ghdl/ghdl

    2,759Vezi pe GitHub↗

    GHDL is a compiler and simulator for VHDL hardware descriptions. It functions as a multi-pass analysis elaborator that resolves design hierarchies and dependencies to prepare hardware descriptions for simulation or synthesis. The project transforms VHDL source code into executable binaries for high-speed digital design verification and serves as a synthesis tool that converts descriptions into structural netlists compatible with vendor or open-source flows. It also implements the Language Server Protocol to provide static analysis, autocomplete, and code navigation for VHDL files. The toolse

    Ensures VHDL designs meet specifications through the use of assertions and code coverage tools.

    VHDLcompilergccghdl
    Vezi pe GitHub↗2,759
  1. Home
  2. Testing & Quality Assurance
  3. Test Suite Execution
  4. Code Correctness Verifications

Explorează sub-etichetele

  • Emission VerificationsAssertions verifying that specific values were emitted from a stream at specific timestamps. **Distinct from Code Correctness Verifications:** Distinct from Code Correctness Verifications: specifically targets the timing and sequence of emitted values in a stream rather than general code output.
  • Hardware Core Verifications1 sub-tagVerification of hardware implementations using testbenches and simulators to ensure architectural compliance. **Distinct from Code Correctness Verifications:** Focuses on the correctness of the hardware processor core rather than the correctness of generated software code
  • Theoretical Derivation VerificationsVerifying the correctness of mathematical proofs by comparing them against functional code execution. **Distinct from Code Correctness Verifications:** Distinct from generic code correctness as it specifically validates the alignment between mathematical theory and executable logic.