KSCrash is a C++ crash reporting library and remote reporting framework designed to capture application crashes and signals. It functions as an async-safe crash reporter that traps exceptions and deadlocks to ensure reports are generated during critical failures.
الميزات الرئيسية لـ kstenerud/kscrash هي: Crash Reporters, Main Thread Responsiveness Monitoring, Symbol Demanglers, System Signal Handling, Application Stability Monitoring, Application Crash Logging, Zombie Object Tracking, Memory Corruption Debugging.
تشمل البدائل مفتوحة المصدر لـ kstenerud/kscrash: acra/acra — Acra is an Android crash reporting framework and diagnostic data collector designed to detect failures and capture… mozilla-firefox/firefox — Firefox is a cross-platform web browser engine designed to render web content, execute JavaScript, and manage secure… countly/countly-server — Countly is a self-hosted product analytics and engagement platform that tracks user behavior across mobile, web, and… iqiyi/xcrash — xCrash is an Android crash reporting SDK and diagnostic tool designed to monitor application health. It captures Java… firebase/quickstart-js — This project is a collection of reference implementations, sample code, and starter kits for integrating Firebase… markzhai/androidperformancemonitor — AndroidPerformanceMonitor is a diagnostic library and debugging tool designed to detect UI freezes and monitor main…
Acra is an Android crash reporting framework and diagnostic data collector designed to detect failures and capture device diagnostics, system logs, and application state. It serves as an embeddable library for capturing and processing crash reports, providing a pipeline to send this data to custom backends or via email. The project features a plugin-based sender architecture that allows reports to be routed through HTTP endpoints, email clients, or proprietary backend implementations. It includes a user-controlled reporting system with preference toggles and interactive dialogs to manage user
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Countly is a self-hosted product analytics and engagement platform that tracks user behavior across mobile, web, and desktop applications. It collects and analyzes device properties, user actions, and session lifecycle data to understand engagement patterns, while also providing crash reporting, push notification delivery, and A/B testing capabilities. The platform is designed for privacy-first deployment, with built-in consent management and the ability to run entirely on private infrastructure. The platform distinguishes itself through its comprehensive feature set that combines analytics w
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