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Rewriting error stacks to preserve the call site and execution history across event loop turns.
Distinct from Asynchronous Debugging Toolkits: Focuses specifically on the reconstruction of the stack trace itself, while the parent is a broader toolkit for debugging.
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q is a JavaScript promise library and asynchronous flow controller designed to manage non-blocking operations. It serves as a system for coordinating parallel tasks and sequencing asynchronous workflows through task chaining and error propagation. The library distinguishes itself with specialized debugging tools that capture long stack traces across asynchronous jumps and monitor unhandled rejections to prevent silent failures. It also functions as a remote object proxy, forwarding method calls to remote targets and routing responses back through promises. The project provides comprehensive
Rewrites error stack traces to track execution across asynchronous jumps and find the origin of failures.
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
Reconstructs calling chains across asynchronous boundaries to recover lost context in callbacks and promises.
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
Retrieves and assembles full call stacks from profiling data using frame and callsite identifiers.