Projects sharing features with Hotspot

Samply is a cross-platform CPU sampling profiler and performance analysis utility. It consists of a command-line tool for recording process stack traces at regular intervals and a visual interface for analyzing the resulting execution data. The system includes a debug symbol resolver that maps raw memory addresses to human-readable function names using local or remote symbol information. It transforms recorded execution data into flame graphs and timelines to pinpoint function-level hotspots. The tool provides capabilities for CPU execution recording, stack unwinding, and symbol resolution a

Tracy is a real-time performance profiling framework for C and C++ applications. It provides a software instrumentation library that captures high-resolution telemetry data, which is then visualized through a separate graphical interface to identify bottlenecks and resource allocation issues. The system utilizes a client-server architecture that enables remote profiling, allowing performance data to be captured on a target machine and analyzed on a workstation. It employs lock-free event logging and shared-memory ring buffers to minimize the overhead of data collection, ensuring that the main

BCC is an eBPF development toolkit and tracing framework used for monitoring and analyzing the Linux kernel. It functions as a performance analysis tool and debugging utility to capture system events, measure kernel latency, and provide network observability. The project distinguishes itself by providing a build system that integrates with LLVM to compile C-like code into BPF bytecode at runtime. It utilizes BPF Type Format data for relocations to maintain cross-kernel compatibility and extracts kernel headers to ensure the generated programs match the specific kernel version. The toolkit co

Speedscope is a web-based performance profiler that visualizes profiling data through interactive flamegraphs and timeline views. It ingests performance profiles from a wide range of sources, including Chrome, Firefox, Safari, Node.js, .NET Core, Instruments, Hermes, GHC, and Ruby, normalizing them into a common schema for unified analysis. The tool distinguishes itself with a canvas-based rendering engine that draws flamegraphs without DOM nodes for each frame, and a WebAssembly-based rendering pipeline for high-performance drawing. It offers left-heavy stack sorting to surface the most time

Arthas is a Java diagnostic tool and runtime debugger designed for real-time troubleshooting of applications. It functions as a remote diagnostics agent that allows users to inspect the runtime state of a Java process, including its heap objects and classloader hierarchies, without requiring a process restart. The project distinguishes itself through advanced bytecode manipulation capabilities, enabling live class hotswapping and the modification of bytecode in running processes. It supports in-memory source compilation and runtime bytecode decompilation to verify and update logic instantly w

This project is a comprehensive technical guide and diagnostic manual for analyzing memory, performance, and asynchronous behavior within Node.js applications. It provides detailed methods for asynchronous tracing, memory diagnostics, and performance analysis to resolve runtime errors and execution bottlenecks. The resource distinguishes itself by covering advanced diagnostic workflows, including the use of flame graphs for CPU profiling, the capture and comparison of heap snapshots for memory leak detection, and the mapping of asynchronous call stacks. It also provides technical guidance on

Bloaty is a binary size profiler and executable format analyzer that attributes every byte of a binary to specific symbols or compile units. It functions as a compilation unit profiler and C++ symbol demangler, mapping binary size back to source files and translating mangled names into human-readable formats. The project distinguishes itself as a binary diffing tool capable of comparing two versions of a binary to isolate specific symbols or sections responsible for size regressions. It provides specialized support for recovering symbols in stripped binaries by associating them with external

Booster is an Android app build optimizer and bytecode manipulator designed to reduce binary size, fix system-level crashes, and improve application performance. It functions as an extensible build process plugin that modifies compiled class files and build artifacts to inject stability fixes and optimizations without altering the original source code. The project differentiates itself through low-level bytecode manipulation to patch OS-level bugs and manage thread pools during the compilation phase. It also provides a performance profiling toolkit to identify main-thread blocking operations

The diagnostics project provides a cross-platform diagnostic infrastructure and command-line toolkit for monitoring runtime performance, analyzing memory dumps, and troubleshooting applications. It features a custom inter-process communication protocol for command and telemetry exchange across platforms, a low-overhead event pipe mechanism for streaming real-time diagnostic events and performance counters from running processes, and automated remote symbol resolution for stack trace analysis. The platform includes native debugger extensions that integrate with standard debuggers to inspect ma

go-torch is a profiling tool for capturing the execution state of Go programs and transforming raw binary data into visual representations of program performance. It functions as a flame graph profiler and performance visualization utility that identifies expensive code paths through the collection of CPU and memory stack traces. The tool features a network-capable remote process profiler that connects to endpoints to capture and export execution profiles from Go binaries. It utilizes stochastic profiling to synthesize execution data into call graphs, allowing for the identification of bottle

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

This project is a Linux system administration question bank designed to evaluate knowledge of server management. It serves as a technical reference and study guide through a collection of curated questions and answers. The resource provides targeted preparation for technical interviews and professional exams. It specifically covers DevOps interview preparation, including containerization, continuous integration, and version control. The knowledge base spans several core competency areas, including system internals, kernel architectures, and the Linux boot process. It also includes materials

This project is a performance analysis suite for Python applications, providing tools for both application-wide profiling and granular code benchmarking. It enables developers to identify execution bottlenecks and measure function call frequency through a combination of deterministic tracing and statistical sampling methods. The tool distinguishes itself by offering a terminal-based interactive interface that allows for real-time navigation and filtering of complex call stacks. It supports non-intrusive data collection through signal-based process interception, enabling performance monitoring

This is an open-source educational website that translates and localizes MIT's Missing Semester course, teaching practical computing skills for computer science students. The curriculum covers developer tooling, shell scripting, version control, security fundamentals, and open-source collaboration, with a focus on core computing skills including data processing pipelines, workflow automation, secure remote access, shell productivity, Vim editing, and Git version control. The project distinguishes itself by teaching command-line mastery, shell scripting, and automation to boost daily developer

backward-cpp is a C++ stack trace library and debugging utility designed to capture, resolve, and print detailed execution traces and crash reports. It functions as a crash reporter and call stack printer that translates raw memory addresses into human-readable function names, filenames, and line numbers. The project provides automated crash reporting by registering system handlers for fatal errors, such as segmentation faults, to automatically generate execution traces upon program failure. It distinguishes itself by extracting source file fragments from disk to display specific lines of cod

vprof is a visual profiling tool for Python designed to identify execution bottlenecks and monitor memory consumption. It functions as a CPU and memory profiler that transforms performance data into interactive visualizations to analyze processor time and call stacks. The project distinguishes itself through a suite of visual diagnostics, including flame graphs for stack visualization and heatmaps that map execution frequency and duration directly onto source code. It also includes a remote performance monitor capable of capturing function-specific metrics from a running server and streaming

The 1BRC (One Billion Row Challenge) is a Java performance benchmarking exercise that processes one billion temperature records from a text file to compute the minimum, mean, and maximum temperature per weather station. At its core, it is a large-scale data aggregation challenge designed to test how efficiently a Java program can parse and aggregate structured data from a plain text file, serving as both a programming exercise and a benchmark for Java performance optimization. The project distinguishes itself through a collection of performance-oriented architectural patterns for high-through

The project is a development kit and compilation toolchain that builds C and C++ source files into native machine code libraries and shared library packages for mobile execution. It integrates target architecture toolchains with standard build systems to transform source code into deployable native modules. The toolset includes debugging and profiling capabilities that bridge low-level system debuggers with compiled binaries to inspect runtime execution states, register contents, and memory layouts. It provides performance monitoring instrumentation to measure execution bottlenecks and resour

Excelize is a library for reading and writing spreadsheet files in the Office Open XML format. It provides a comprehensive suite of tools for programmatically creating, modifying, and analyzing workbooks, worksheets, and cell data, ensuring compatibility across various office software suites through structured XML serialization. The library distinguishes itself with a built-in formula calculation engine that evaluates complex mathematical and logical expressions directly against workbook data. It also features a memory-mapped streaming architecture, which allows for the efficient processing o

gperftools is a collection of specialized tools for profiling CPU usage, detecting memory errors, and providing high-performance memory allocation. It provides a memory profiling toolkit for C++ applications, including a sampling CPU profiler and a heap profiler for analyzing consumption patterns. The project includes a high-performance memory allocator designed as a multi-threaded replacement for standard allocation to reduce contention and improve execution speed. It further provides a memory debugger to identify illegal memory access and double frees. The toolkit covers broad diagnostic c

Async-profiler is a suite of performance tools designed for sampling Java runtimes, tracking memory allocations, and monitoring hardware counters. It functions as a low-overhead sampling profiler for Java applications, collecting stack traces and memory allocation data without safepoint bias. The project provides specialized utilities for generating interactive flame graphs to visualize execution hotspots in a web browser. It includes a hardware performance counter monitor to track low-level system events such as cache misses and page faults. The toolset covers several diagnostic domains, in

Coz is a suite of profiling tools for C++ applications designed to identify performance bottlenecks through causal analysis and execution tracking. It functions as a performance profiler that tracks operation timing and execution frequency to determine critical paths within a system. The tool distinguishes itself through a causal profiling engine and an optimization simulation engine. These capabilities allow for the prediction of how hypothetical code improvements would impact overall system throughput and latency by simulating the effects of speedups without requiring the software to be rew

Matrix is a suite of mobile application performance management and analysis tools. It provides a plugin-based monitoring system for capturing crashes, lags, and memory leaks, alongside a static binary auditor for reducing installation package size and a bytecode instrumentation tool for performance tracking. The project distinguishes itself through native memory debugging and a SQLite query linter that identifies inefficient database patterns. It employs native interception techniques to detect memory leaks and heap corruption without requiring source code recompilation, and uses a custom run

Perfetto is a platform for system-level performance tracing and analysis on Linux and Android. It combines a high-throughput trace recorder, a SQL-based query engine, and a browser-based visualizer into a single toolchain. The platform covers CPU scheduling and call-stack profiling, native and Java heap memory allocation tracking, GPU and graphics events, and system-wide counters such as CPU frequency and power consumption. The architecture decouples trace recording from offline analysis, using a compact protobuf format for event encoding and columnar storage for efficient SQL queries. The we

Memory Profiler is a diagnostic library for Ruby applications designed to monitor runtime memory consumption and object lifecycles. It provides tools to track object allocations and memory usage, enabling the identification of performance bottlenecks and potential memory leaks that affect software stability. The tool functions by observing memory behavior during program execution, allowing developers to distinguish between short-lived data and objects that persist beyond their intended lifecycle. It captures the execution context of allocations by walking the call stack, which helps attribute

Node-clinic is a performance profiling suite for Node.js designed to diagnose CPU bottlenecks, memory leaks, and asynchronous event loop issues. It provides specialized diagnostic tools for visualizing asynchronous flows, generating CPU flame graphs, and analyzing heap memory allocation. The suite includes a CPU flame graph tool to identify functions consuming the most processing time, a heap memory analyzer to track object allocation and leaks, and an asynchronous I/O profiler to map operation flows and find event loop bottlenecks. These tools cover broader capabilities in CPU execution pro

Bistoury is a production diagnostics tool for Java applications that provides a distributed debugging console, a performance profiler, and a runtime bytecode manipulator. It enables real-time application debugging and production diagnostics by analyzing running Java applications through dynamic instrumentation and state inspection. The system distinguishes itself through a remote agent manager that coordinates diagnostic connections and a runtime bytecode manipulator capable of redefining classes in memory without requiring process restarts. It features a web interface for capturing heap dump