gimli is a Rust library for reading and writing the DWARF debugging format, used by debuggers, profilers, and binary analysis tools. It provides zero-copy, lazy parsing of all standard DWARF sections (e.g., .debug_info, .debug_line, .debug_frame, .debug_names) across versions 2–5, including split DWARF (DWO/DWP) and supplementary object files. The library is split into `read` and `write` modules, with a conversion pipeline to transform parsed debug data back into DWARF. It is designed to be `no_std` compatible (with alloc) and uses trait-based abstractions for readers/writers, allowing custom backing stores. Example CLI tools (dwarfdump, simple, convert) demonstrate real-world usage. The codebase is highly modular, with extensive unit tests, fuzzing, and benchmarks, and emphasizes correctness, performance, and cross-platform support (32/64-bit, little/big endian).
Coz is a causal profiler for native code (C/C++, Rust, Go, Swift, Java) that uses virtual speedup experiments to identify which lines of code, if optimized, would most improve program throughput or latency. It operates by injecting a shared library (libcoz) via LD_PRELOAD or DYLD_INSERT_LIBRARIES, interposing synchronization primitives to track blocking and apply controlled delays on non-selected threads. The profiler outputs a JSON Lines profile that can be visualized with a built-in web viewer (D3.js scatter plots with loess smoothing) or analyzed via CLI. It includes an AI-assisted feature for suggesting progress point placement and optimization advice. The architecture is a hybrid: a core runtime library in C++ with language bindings for Rust, Go, Swift, and Java (JVMTI agent), plus a Python CLI that orchestrates profiling, visualization, and LLM integration. The project is a research artifact from UMass Amherst, published at SOSP 2015, and remains actively developed with modern features like streaming AI support.