14 repositorios
Methodologies for evaluating and balancing system latency and throughput.
Distinct from Latency Optimization: Candidates were either tool-specific or AI-focused; this tag covers the fundamental architectural trade-off analysis.
Explore 14 awesome GitHub repositories matching software engineering & architecture · Performance Analysis. Refine with filters or upvote what's useful.
This project is a comprehensive Java backend engineering guide and technical reference focused on high-concurrency design, distributed systems, and microservices architecture. It provides detailed strategies for decomposing monolithic applications, managing service discovery, and implementing the architectural patterns required for scalable backend environments. The repository distinguishes itself through an extensive collection of big data algorithmic references and database scaling strategies. It covers memory-efficient techniques for analyzing massive datasets, such as Top-K element extrac
Analyzes call counts and latency percentiles across request chains to evaluate system throughput and responsiveness.
Forem is an open-source platform designed for building and managing technical communities. It functions as a social publishing engine that enables members to share long-form content, participate in threaded discussions, and engage through social interactions. The platform provides tools for organizations to maintain branded profiles, host community hackathons, and facilitate collaborative learning through structured educational tracks. Beyond its social features, Forem integrates advanced capabilities for AI agent workflow orchestration and codebase knowledge graphing. It allows developers to
Optimizes performance by tracking file changes and re-analyzing only modified code.
Strix is an automated security research and vulnerability scanning platform that leverages language models to orchestrate complex security analysis tasks. It functions as a comprehensive framework for penetration testing and continuous security integration, allowing users to embed automated vulnerability research directly into development pipelines or execute it within isolated, containerized environments. The platform distinguishes itself through a multi-agent orchestration engine that coordinates specialized autonomous agents to perform parallel security assessments. By integrating LLM-agno
Identifies security vulnerabilities introduced in recent commits by comparing current code against a base reference.
This project is a high-performance static type checker and comprehensive development toolkit for Python. It functions as a core analysis engine that identifies type inconsistencies and enforces code correctness, while simultaneously providing a language server implementation to deliver real-time diagnostics and intelligence directly within development environments. The tool distinguishes itself through a parallelized execution engine that maximizes performance across large-scale codebases and monorepo structures. It supports gradual type adoption, allowing developers to integrate type checkin
Performs incremental re-analysis of modified code to provide rapid feedback during development.
HowToBeAProgrammer is a comprehensive software engineering career guide and professional development framework. It serves as a curated-knowledge repository and handbook designed to help programmers acquire technical habits and social competencies necessary for professional advancement. The project distinguishes itself by integrating technical craftsmanship with a detailed manual for technical leadership and organizational navigation. It provides specific strategies for career progression, such as compensation negotiation, promotion readiness, and the management of professional boundaries to p
Explains how to use profiling tools and logs to analyze system performance and locate expensive I/O.
Infer is a static analysis toolset for Java, C, C++, and Objective-C designed to detect memory leaks, null dereferences, and resource bugs. It functions as a multi-language bug finder that identifies race conditions, deadlocks, and memory safety issues by translating source code into a common intermediate representation for analysis. The project distinguishes itself through an inter-procedural data flow analyzer that tracks movement between sources and sinks to detect tainted flows and generate data flow graphs. It also includes a framework for verifying temporal properties and reachability u
Utilizes an incremental analysis engine to process only modified code segments, significantly reducing continuous integration time.
Semgrep is a static analysis security testing tool designed to identify vulnerabilities and logic errors by matching source code against declarative patterns. It functions as an automated scanner that integrates into development workflows to detect insecure code patterns and enforce coding standards before deployment. The engine utilizes a language-agnostic intermediate representation and a modular parser architecture to normalize diverse programming languages into a unified format. This allows for consistent rule execution across different codebases, enabling users to perform custom structur
Optimizes performance by re-analyzing only modified code segments to provide rapid feedback during development.
Pyright is a static type checker for Python designed to validate type hints and identify potential errors within large codebases. It functions as a command-line utility that integrates into local development environments and continuous integration pipelines to ensure code quality and consistency. The tool distinguishes itself through a high-performance analysis engine that utilizes incremental dependency graph analysis and persistent state caching to re-evaluate only the affected portions of a project. By implementing the Language Server Protocol, it provides real-time feedback, including err
Optimizes analysis performance by tracking dependency relationships and re-evaluating only modified code segments.
Scalene is a high-performance diagnostic utility designed to measure resource consumption during the execution of Python applications. It functions as a line-level monitor, providing granular insights that pinpoint the specific source code responsible for performance overhead. The tool distinguishes itself through statistical profiling that captures stack traces and resource usage without requiring manual instrumentation of the source code. It tracks CPU, GPU, and memory consumption by intercepting library-level calls and hardware driver commands, allowing for the analysis of both managed and
Evaluates the performance of complex applications to determine which functions or code blocks are slowing down the overall system.
Xray is a security assessment tool focused on web vulnerability scanning, attack surface mapping, and technology fingerprinting. It identifies common security flaws through automated scanning and semantic analysis, while verifying findings via a custom proof-of-concept execution engine. The system distinguishes itself with a containerized vulnerability testbed used to deploy pre-configured vulnerable applications. This environment allows for the simulation of specific vulnerabilities and edge-case scenarios to validate scanner accuracy and eliminate false positives. The platform covers a bro
Uses a semantic analysis engine to detect vulnerabilities by matching request and response patterns against known flaw signatures.
Wuzz is an interactive command line HTTP client and request inspector designed for capturing, reviewing, and analyzing outgoing network calls and their payloads. It functions as a terminal-based tool for debugging API issues and testing web endpoints. The tool provides specialized filtering for response bodies, using regular expressions and format-specific query syntaxes tailored for JSON and HTML data. It allows for the persistence of captured requests and responses to disk to facilitate the reproduction of network issues and offline analysis. User settings and default request behaviors are
Writes captured HTTP requests and responses to files to facilitate later retrieval and detailed analysis.
Error Prone is a static code analyzer and Java compiler extension that identifies common programming mistakes during the build process. It functions as a compiler wrapper that flags potential errors as compile-time failures to prevent bugs from reaching execution. The tool integrates directly into the Java compilation workflow to provide compile-time validation. It allows for the definition of custom linting rules and analysis checks to enforce specific coding standards and detect prohibited API usage. The system utilizes abstract syntax tree analysis and type-aware pattern matching to inspe
Optimizes analysis performance by re-examining only modified source files across builds.
Phan es un analizador estático y verificador de tipos para PHP que identifica errores e incompatibilidades de tipo sin ejecutar el código. Sirve como una puerta de calidad para pipelines de integración continua y una herramienta para verificar la seguridad de tipos, comprobando específicamente tipos de unión, genéricos y formas de array. El proyecto se distingue por el uso de un demonio en segundo plano y una implementación del Protocolo de Servidor de Lenguaje (LSP), que proporcionan diagnósticos y navegación en tiempo real dentro de los editores. También cuenta con un sistema de supresión basado en línea base que permite a los desarrolladores registrar errores existentes en un archivo de instantánea para centrarse exclusivamente en nuevas regresiones. El motor de análisis cubre una amplia gama de capacidades, incluyendo la detección de código muerto, la validación de compatibilidad de lenguaje a través de diferentes versiones de PHP y la inferencia de tipos de variables y plantillas. Admite análisis extensible a través de un sistema de plugins y proporciona correcciones de código automatizadas para un subconjunto de problemas detectados. Los usuarios pueden iniciar el proceso generando un archivo de configuración con niveles de rigor seleccionables para validar gradualmente su base de código.
Optimizes performance by re-analyzing only modified files and their affected dependencies.
Este proyecto es un framework de benchmarking de rendimiento y probador de estrés de protocolos de red diseñado para evaluar la estabilidad del sistema bajo condiciones de alta concurrencia. Funciona como una utilidad de línea de comandos que simula volúmenes masivos de solicitudes simultáneas para identificar cuellos de botella en la infraestructura y verificar la confiabilidad del servicio. La herramienta se distingue por su orquestación agnóstica al protocolo, lo que permite pruebas de carga a través de diversos estándares incluyendo HTTP, WebSocket, gRPC y Radius. Soporta configuraciones de solicitud complejas, permitiendo a los usuarios inyectar encabezados personalizados, datos binarios y payloads externos para replicar comportamientos de cliente variados. Para garantizar la integridad de los datos durante las pruebas de estrés, el framework utiliza middleware de validación conectable que ejecuta lógica personalizada contra las respuestas del servidor en tiempo real. Más allá de la generación de carga básica, la herramienta proporciona una observabilidad integral agregando métricas de rendimiento en flujos en vivo para monitorear el throughput, la latencia y las distribuciones de error. Genera informes estadísticos detallados y se integra con servicios de inteligencia externos para proporcionar análisis y puntuación automatizados del rendimiento del sistema. El software se configura y gestiona completamente a través de parámetros de línea de comandos, facilitando la integración en flujos de trabajo de pruebas automatizados.
Generates detailed statistical reports and uses intelligent scoring to evaluate system latency, throughput, and error rates during high-load scenarios.