8 projects for "test coverage" with 2 filters applied:

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  • 1
    urllib3

    urllib3

    Python HTTP library with thread-safe connection pooling

    ...File uploads with multipart encoding. Helpers for retrying requests and dealing with HTTP redirects. Support for gzip, deflate, brotli, and zstd encoding. Proxy support for HTTP and SOCKS. 100% test coverage. Professional support for urllib3 is available as part of the Tidelift Subscription. Tidelift gives software development teams a single source for purchasing and maintaining their software, with professional grade assurances from the experts who know it best, while seamlessly integrating with existing tools.
    Downloads: 0 This Week
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  • 2
    Symfony PHPUnit Bridge

    Symfony PHPUnit Bridge

    Provides utilities for PHPUnit

    Symfony PHPUnit Bridge is a tool that facilitates unit and functional testing within Symfony applications. It enhances PHPUnit’s capabilities by providing better integration, including improved error reporting and test isolation. The bridge supports deprecation notices, legacy code compatibility, and automatic configuration for running tests efficiently.
    Downloads: 0 This Week
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  • 3
    Expat

    Expat

    Fast streaming XML parser written in C99 with >90% test coverage

    Welcome to Expat, a stream-oriented XML parser library written in C. Expat excels with files too large to fit RAM, and where performance and flexibility are crucial. There are a number of applications, libraries, and hardware using Expat, as well as bindings and 3rd-party wrappers. Expat is packaged everywhere. This is Expat, a C99 library for parsing XML 1.0 Fourth Edition, started by James Clark in 1997. Expat is a stream-oriented XML parser. This means that you register handlers with the...
    Downloads: 11 This Week
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  • 4
    JavaScript & Node.js Testing

    JavaScript & Node.js Testing

    Comprehensive and exhaustive JavaScript & Node.js testing

    This project compiles practical advice for testing JavaScript applications across the stack, emphasizing clarity, speed, and reliability over dogma. It distinguishes between different kinds of tests—unit, integration, end-to-end—and shows when each is appropriate given time and risk constraints. The guide focuses on removing flakiness by isolating side effects, controlling randomness, and stabilizing async code paths. It also demonstrates test design techniques like arranging test data,...
    Downloads: 0 This Week
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  • 5
    Monix

    Monix

    Asynchronous, Reactive Programming for Scala and Scala.js

    Monix is a high-performance, reactive, and asynchronous programming library for Scala and Scala.js. Built as a Typelevel project, it provides advanced abstractions like Task, Observable, Iterant, and Coeval, enabling compositional, back-pressure‑aware event-driven systems that integrate cleanly with Cats Effect and Reactive Streams.
    Downloads: 2 This Week
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  • 6
    Big List of Naughty Strings

    Big List of Naughty Strings

    List of strings which have a high probability of causing issues

    The Big List of Naughty Strings is a community-maintained catalog of “gotcha” inputs that commonly break software, from unusual Unicode to SQL and script injection payloads. It exists so developers and QA engineers can easily test edge cases that normal test data would miss, such as zero-width characters, right-to-left marks, emojis, foreign alphabets, and long or malformed strings. By throwing these strings at forms, APIs, databases, and UIs, teams can discover encoding bugs, sanitizer...
    Downloads: 0 This Week
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  • 7
    XcodeCoverage

    XcodeCoverage

    Code coverage for Xcode projects (Objective-C only)

    XcodeCoverage is a tool that automates the generation of code coverage reports for iOS and macOS projects. It helps developers measure how much of their code is tested, facilitating better testing practices and coverage improvement.
    Downloads: 0 This Week
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  • 8
    benchm-ml

    benchm-ml

    A benchmark of commonly used open source implementations

    This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different...
    Downloads: 0 This Week
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