# compilation Published articles for compilation. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## From error mitigation to fault-tolerant quantum computing DevFeed: [From error mitigation to fault-tolerant quantum computing]() Original publisher: [Read original article]() Published: 2026-09-15T14:30:00Z Content type: article Language: en Sources: [IBM Research]() Topics: [Quantum Computing](), [Hardware](), [ibm]() Tags: [compilation](), [deep-dive](), [errors](), [hardware](), [quantum](), [quantum-computing](), [quantum-error-correction-mitigation](), [quantum-software](), [real-time](), [reduce](), [resource]() ### AI overview The article describes a continuum from quantum error mitigation to quantum error correction as a path toward useful quantum computing. It reports emerging techniques with lower effective error rates, reduced sampling overhead, and lower resource requirements than conventional approaches. ### Source excerpt A spectrum of error-correcting techniques is enabling useful quantum computation, measured not by logical qubits but by the circuits you can run with them. ## Build Hints That Fail Before the Build Server DevFeed: [Build Hints That Fail Before the Build Server]() Original publisher: [Read original article]() Author: Shai Almog Published: 2026-09-02T00:00:00Z Content type: article Language: en Sources: [CodeName One]() Topics: [Compiler](), [Java](), [configuration]() Tags: [autocomplete](), [build](), [compilation](), [compiler](), [configuration](), [java]() ### AI overview Codename One moves 87 common build hints into Java annotations so the compiler can catch misspelled names, incorrect value types, and unsupported options before builds reach the server. The change preserves the existing key-and-string format used by older projects and the build service. ### Source excerpt Codename One now exposes 87 common build hints as Java annotations, giving the compiler enough information to reject misspelled names, wrong types, and unsupported values before a build reaches the server. ## Experiment in reducing target directory size on nightly DevFeed: [Experiment in reducing target directory size on nightly]() Original publisher: [Read original article]() Author: Jakub Beránek Published: 2026-08-18T00:00:00Z Content type: article Language: en Sources: [Inside Rust Blog]() Topics: [Rust](), [Compiler](), [data]() Tags: [compilation](), [compiler](), [disk-space](), [information](), [rust](), [space](), [state]() ### AI overview The Cargo Team is testing -Zembed-metadata=no by enabling it by default on the nightly channel. The experiment aims to reduce Rust target directory size by avoiding duplicated crate metadata in build artifacts, while gathering feedback about viability and user impact. ### Source excerpt TL;DR: The Cargo Team will be rolling out an experiment to identify user impact for a proposed change. Cargo will enable the -Zembed-metadata=no feature on the nightly channel by default, which can help reduce the size of the target directory somewhat. This is an experiment designed to gather feedback about viability of this feature. Users are not expected to migrate to support this feature, but to report any issues and opt-out if needed in the meantime. What is this about? High disk usage of Rust compilation artifacts is frequently cited as one of the biggest annoyances of Rust users. In our 2025 State of Rust survey, it was actually the second most commonly reported problem, right after compilation speed. There are various reasons why the target directory can become quite large, such as: Cargo compiles the whole crate graph from scratch by default, which produces a lot of build artifacts. Debug information takes a lot of disk space. Incremental compilation artifacts take a lot of disk space. While you can disable debug information or incremental compilation to reduce the target directory size, that of course comes with severe trade-offs in compilation speed and debuggability of your program. However, there is one source of data in the target directory that currently takes too much size even though it doesn't really have to. It is the "crate metadata", which can be duplicated across multiple files. We will focus on that in this blog post. What causes duplicated (meta)data For years, Cargo has been using pipelined compilation to speed up building of crate graphs. When compiling a library crate, it tells the compiler to produce an .rmeta file (which contains all the crate metadata required to use this library) as soon as possible, even before having the final executable code available. This enables dependent crates to start compiling sooner. However, once the library does finish compiling, the final produced .rlib file will contain both the executable code and the Ru ## Compiling to intermediate representation: Write yourself a compiler, Part III DevFeed: [Compiling to intermediate representation: Write yourself a compiler, Part III]() Original publisher: [Read original article]() Published: 2026-08-16T22:00:00Z Content type: tutorial Language: en Sources: [Tomasz Nurkiewicz around Java and concurrency]() Topics: [Compiler](), [virtual machines](), [Code](), [WebAssembly](), [Java]() Tags: [assembly](), [bytecode](), [compilation](), [compiler](), [go](), [interpreter](), [ir](), [javascript](), [python](), [virtual-machines](), [webassembly](), [writing-compiler]() ### AI overview This tutorial explains how a small interpreter project evolves into a compiler by emitting intermediate representation (IR). It contrasts interpreted and compiled languages, describes bytecode and virtual machines, and uses Java and WebAssembly examples to show how IR instructions are executed. ### Source excerpt It's time to dive a bit deeper and abandon the naive realm of interpreters. Our tiny little project can finally call itself a compiler. In this part we'll emit so-called intermediate representation instead of just evaluating and running the source code as-is. OK, what does this all mean? ## C++ libraries linking DevFeed: [C++ libraries linking]() Original publisher: [Read original article]() Author: Nenad Rakocevic (noreply@blogger.com) Published: 2026-07-29T19:07:38Z Content type: release Language: en Sources: [Red]() Topics: [Red](), [C++](), [toolchain]() Tags: [build](), [build-tools](), [c-plus-plus](), [clang](), [compilation](), [directx](), [gcc](), [libraries](), [linux](), [macos](), [msvc](), [static-linking](), [toolchain](), [windows](), [x86]() ### AI overview The Red toolchain now supports statically linking C++ libraries, including their runtime, on Windows, Linux, and macOS. It accepts libraries built with MSVC, GCC, or clang through the existing import system and compilation switch, with platform-specific prerequisites and constraints. ### Source excerpt When we introduced static linking of C libraries, the promise was simple: name a .lib or .a archive in your #import, compile with -s, and ship one self-contained executable, no DLLs riding along, nothing to install on the target machine. There was one big frontier left, and everyone saw it coming: the libraries people want most (vision, GUI, audio, machine learning) are written in C++. A C++ library is a very different animal to link: it brings global constructors, exceptions, RTTI, templates, thread-local storage, and an entire language runtime that expects to be wired up just so. Until now, that was the line where you switched back to DLLs. That line is gone. The Red toolchain now statically links C++ libraries too (their runtime included) on every platform Red targets: Windows, Linux (x86 and ARM), and macOS. The best part: nothing changes. It is the same import system and same compilation switch: red -r -s myapp.red Libraries built with MSVC, GCC or clang are all accepted, in their native object formats. What you need preinstalled ➤ Windows: for C++ libraries (or C code built against Microsoft's static runtime), install the free Visual Studio Build Tools with the "Desktop development with C++" workload. Just one installer, and Red locates everything by itself: no vcvarsall, no PATH, no environment variables. Plain C libraries still need nothing at all and that now extends to C libraries touching COM, DirectX or MediaFoundation: the GUID constants such code references ship inside the toolchain, so a fresh Windows 11 with only red-toolchain executable on it links them! ➤ Linux: the GNU runtime archives from your distribution's gcc packages (libstdc++.a, libgcc.a and friends) placed next to your library. If one is missing, the linker names exactly what it needs. ➤ macOS: nothing beyond the toolchain; the system C++ runtime binds automatically. Some constraints 32-bit libraries for now, until the 64-bit toolchain is ready. The imported surface must be C (extern "C", ## GC and Exceptions in Wasmtime DevFeed: [GC and Exceptions in Wasmtime]() Original publisher: [Read original article]() Author: Nick Fitzgerald Published: 2026-07-20T00:00:00Z Content type: release Language: en Sources: [Bytecode Alliance]() Topics: [WebAssembly](), [wasm](), [Exception](), [toolchains]() Tags: [compilation](), [exceptions](), [release](), [toolchains](), [wasm](), [webassembly]() ### AI overview Wasmtime 47 enables the Wasm GC and exceptions proposals by default. The article explains how Wasm GC supports languages with object-and-reference data models by letting the runtime manage types and lifetimes, while the exceptions proposal provides more efficient exception handling for WebAssembly compilation targets. ### Source excerpt The Wasm GC and exceptions proposals are both enabled by default in today's Wasmtime 47 release! We are excited to help bring more languages to WebAssembly and everywhere that Wasmtime runs. Getting to this point involved large Wasmtime changes and represents the culmination of years of engineering effort. ## AI RPG Migration Can Compile and Still Break Business Logic DevFeed: [AI RPG Migration Can Compile and Still Break Business Logic]() Original publisher: [Read original article]() Author: Federico Tomassetti Published: 2026-06-30T08:00:00Z Content type: opinion Language: en Sources: [Federico Tomassetti]() Topics: [migration](), [AI-assisted coding](), [Benchmark](), [Code]() Tags: [ai](), [benchmarks](), [business-logic](), [compilation](), [legacy-modernization](), [migration](), [rpg](), [tests]() ### AI overview The article argues that AI-assisted RPG migration tools should be evaluated on behavioral equivalence, not only compilation and generated test-pass rates. It cites the AgentModernize study, where the best reported result reached 19.4% behavioral equivalence, and describes gaps between extracting business rules and implementing them faithfully. ### Source excerpt AI-assisted RPG migration tools report high compilation success rates while silently failing on behavioral equivalence -- packed decimal truncation, activation group persistence, and cycle logic. The benchmarks show why, and what a real accuracy test looks like. The post AI RPG Migration Can Compile and Still Break Business Logic appeared first on Federico Tomassetti. ## Codename One Compiles Java and Kotlin Apps to Native Windows Executables Without a JVM DevFeed: [Codename One Compiles Java and Kotlin Apps to Native Windows Executables Without a JVM]() Original publisher: [Read original article]() Author: Shai Almog Published: 2026-06-15T00:00:00Z Content type: article Language: en Sources: [CodeName One]() Topics: [Java](), [Windows](), [win32](), [Arm]() Tags: [binaries](), [compilation](), [desktop](), [java](), [native](), [win32](), [windows]() ### AI overview Codename One's new Windows port uses the ParparVM pipeline to compile Java and Kotlin bytecode into standalone native Win32 executables without bundling or installing a JVM. The build targets both x64 and arm64 Windows systems. ### Source excerpt The new native Windows port compiles your Java to a standalone Win32 executable through ParparVM, Direct2D, and DirectWrite. No JVM, no bundled runtime, a 5MB hello world, and both x64 and arm64 from one build. ## Achieving Fast Inner Dev Loops with Gradle: Configuration Cache and Beyond DevFeed: [Achieving Fast Inner Dev Loops with Gradle: Configuration Cache and Beyond]() Original publisher: [Read original article]() Author: Alex Semin Published: 2026-05-20T04:00:00Z Content type: article Language: en Sources: [The Gradle Blog]() Topics: [Gradle](), [code productivity](), [build performance](), [build times](), [Development]() Tags: [build](), [build-tool](), [compilation](), [context](), [developer-productivity](), [flow](), [gradle](), [incremental](), [kotlinconf](), [parallelism](), [productivity]() ### AI overview This article explains how Gradle is working to accelerate inner developer loops. It describes the shift from execution time to configuration time as the main build bottleneck in large codebases, while highlighting configuration cache, incremental builds, build cache, and parallelism as approaches to reduce waiting and preserve developer flow. ### Source excerpt How many engineers in your organization have to sit idle for 10 or more minutes just to rebuild the app locally after a small change? If you're an engineering leader, build engineer, or part of a developer productivity team, you're not alone in facing this challenge. Building complex software is inherently demanding, but the time your developers spend waiting has a profound impact beyond just the literal minutes lost. It fundamentally disrupts their psychological flow. "There are like these time scales of psychological flow, right? So if something takes longer than a minute, you already start planning for it... you suffer from context switch as well. If it's 1 second, that's where we want to be right in that seamless state of flow. And if it's less than one second, then you feel it's like magic... productive developers are happy developers." -- Rodrigo Oliveira When developers have to wait, their attention drifts, and the cost of context switching destroys their momentum. Our goal as enablers of developer productivity should be to eliminate this friction, bringing that feedback loop as close as possible to the "magical one second". In a recent presentation at KotlinConf 2025, Gradle engineers Rodrigo Oliveira and Alex Semin detailed how Gradle Build Tool is evolving to keep developers in that productive, happy "flow state". By tackling the most significant bottlenecks in modern software builds, Gradle is paving the way for incredibly fast inner developer loops. If you prefer to watch the presentation recording, you can find it here. The shifting bottleneck: From execution to configuration On every invocation, Gradle goes through three distinct phases: initialization, configuration, and execution. Historically, when we optimized Gradle builds, we focused almost exclusively on the execution phase. This is when the majority of work expected by a developer happens: production sources compilation, test execution, etc. For years, execution was the longest phase. We tackled thi ## OpenCL 3.1 is Here DevFeed: [OpenCL 3.1 is Here]() Original publisher: [Read original article]() Author: Khronos Group (webservices@khronosgroup.org) Published: 2026-05-04T07:01:00Z Content type: release Language: en Sources: [Blogs Khronos Blog]() Topics: [cross-platform](), [Compiler](), [Open Source](), [toolchain]() Tags: [2026](), [api](), [blog-openc](), [compilation](), [compiler](), [compilers](), [cross-platform](), [directx](), [embedded](), [enumerate](), [opencl](), [optional](), [source](), [spir](), [vulkan]() ### AI overview The Khronos OpenCL Working Group has released OpenCL 3.1, moving field-proven capabilities into the core specification. The release mandates SPIR-V kernel ingestion for conformant implementations and expands cross-platform availability through a growing implementation, compiler, runtime, and framework ecosystem. ### Source excerpt On the eve of IWOCL 2026, the Khronos® OpenCL Working Group has released OpenCL™ 3.1, bringing widely deployed, field-proven capabilities into the core specification to expand functionality, including SPIR-V ingestion, that developers will be able to rely on across conformant implementations. The new specification arrives into a growing OpenCL ecosystem, with implementations from multiple silicon vendors, particularly in mobile and embedded markets, and higher-level frameworks including SYCL™ and chipStar increasingly targeting OpenCL as an acceleration backend. The open-source compiler and runtime ecosystem around OpenCL also continues to mature with layered implementations of OpenCL over Vulkan and DirectX 12 -- widening OpenCL's cross-platform availability, including on platforms without native drivers. ## Metro 1.0.0 Is Stable as a Kotlin Multiplatform Compile-Time Dependency Injection Framework DevFeed: [Metro 1.0.0 Is Stable as a Kotlin Multiplatform Compile-Time Dependency Injection Framework]() Original publisher: [Read original article]() Author: Zac Sweers Published: 2026-04-27T21:07:22Z Content type: release Language: en Sources: [Zac Sweers]() Topics: [Kotlin](), [Dependency injection](), [multiplatform](), [Compiler](), [Framework](), [gradle-plugin]() Tags: [build-performance](), [build-times](), [compilation](), [compiler](), [dependency-injection](), [experimental](), [gradle](), [gradle-plugin](), [incremental](), [kotlin](), [metro](), [multiplatform](), [open-source](), [perfetto](), [stable]() ### AI overview Metro 1.0.0 is now stable. The Kotlin multiplatform compile-time dependency injection framework uses a compiler plugin and provides API-stable runtime APIs, MetroX artifacts, and a Gradle plugin unless marked experimental. The article also describes build-performance improvements and compile-time validation features. ### Source excerpt New here? Metro is a multiplatform, compile-time dependency injection framework for Kotlin implemented as a compiler plugin. Metro 1.0.0 is out now and stable. This means that its runtime APIs (runtime, MetroX artifacts, Gradle plugin, etc.) are now API-stable unless annotated with an experimental annotation. This ## Unlocking Koin Compile Safety -- Koin Compiler Plugin 1.0.0-RC1 DevFeed: [Unlocking Koin Compile Safety -- Koin Compiler Plugin 1.0.0-RC1]() Original publisher: [Read original article]() Author: Arnaud Giuliani Published: 2026-04-14T08:08:36Z Content type: release Language: en Sources: [Koin developers - Medium]() Topics: [koin](), [Compiler](), [Dependency injection](), [Kotlin](), [Code generation]() Tags: [compilation](), [compiler](), [dependency](), [dependency-injection](), [generation](), [koin](), [kotlin](), [kotlin-multiplatform](), [plugin](), [release](), [safety]() ### AI overview Koin announces Compiler Plugin 1.0.0-RC1 for Kotlin and KMP. The release candidate validates dependency graphs during compilation and adds constructor auto-wiring across DSL and annotations. ### Source excerpt Koin Compiler Plugin 1.0.0-RC1 -- Unlocking Compile-Safe Dependency Injection for Kotlin & KMP Hello Koin Community 👋 Compile-time safety has been one of the most requested features by the community. For years, verifying your Koin dependency graph required runtime tools with checkModules()and verify()in your test suite. They run after compilation. If something is missing, you find out in test results, not at build time. It's now time for new generation of tools for Koin. My Linkedin post for AndroidMakers Last week at Android Makers (Paris, France), we announced Koin Compiler Plugin 1.0.0-RC1! This release candidate brings compile-time safety, constructor auto-wiring, and a unified developer experience for both DSL and Annotations, all powered by a native Kotlin Compiler Plugin. Aligned with Koin 4.2.1 and Kotlin 2.3.20. Check out the roadmap and documentation to get started. Dependency graph validation is done in the Koin Compiler Plugin itself: your graph is verified as part of the build (no need to run tests). DSL, annotations, and even individual call sites are checked. The Kotlin compiler plugin ecosystem has matured, and new DI approaches are emerging. Koin's answer is straightforward: lighter Compiler codegen, an existing runtime container, and validation by design of the compilation. Koin Compiler Plugin -- 1.0.0-RC1Check the online Koin documentation for further information: https://insert-koin.io/docs/intro/koin-compiler-plugin We are also gathering some "playground apps" to showcase different scenarios of Koin Compiler Usages (https://github.com/InsertKoinIO/playground-apps) Koin Compiler Plugin Setup 🔎 Below, you will find the minimum versions of Koin & Koin Compiler Plugin that are allowed to enable compile safety (note that you need Kotlin 2.3.20): [versions] kotlin = "2.3.20" koin = "4.2.1" koin-plugin = "1.0.0-RC1" [libraries] koin-core = { module = "io.insert-koin:koin-core", version.ref = "koin" } # if using annotations koin-annotations = { module = ## A brief history of C/C++ programming languages DevFeed: [A brief history of C/C++ programming languages]() Original publisher: [Read original article]() Author: Daniel Lemire Published: 2026-04-09T14:58:53Z Content type: opinion Language: en Sources: [Daniel Lemire]() Topics: [C](), [C++](), [Programming](), [Java](), [C#](), [Fortran](), [Go Language](), [JavaScript](), [Python]() Tags: [c-c-plus-plus](), [compilation](), [garbage-collection](), [go](), [history](), [languages](), [memory](), [programming](), [programming-languages]() ### AI overview This article presents a brief history of C and C++, explaining how C emerged for low-level systems programming and how C++ added object-oriented, generic, and compile-time metaprogramming features. It then contrasts their portability challenges with Java and discusses JavaScript, Python, C#, and Go. The supplied text ends mid-sentence. ### Source excerpt Initially, we had languages like Fortran (1957), Pascal (1970), and C (1972). Fortran was designed for number crunching and scientific computing. Pascal was restrictive with respect to low-level access (it was deliberately "safe", as meant for teaching structured programming). So C won out as a language that allowed low-level/unsafe programming (pointer arithmetic, direct memory access) ... Continue reading A brief history of C/C++ programming languages ## Supercharging Redpanda Streaming with profile-guided optimization DevFeed: [Supercharging Redpanda Streaming with profile-guided optimization]() Original publisher: [Read original article]() Author: Stephan Dollberg Published: 2026-04-02T00:00:00Z Content type: article Language: en Sources: [Redpanda]() Topics: [Optimization](), [Streaming](), [Latency](), [Compiler](), [LLVM](), [Instrumentation](), [build performance](), [Benchmark]() Tags: [benchmark](), [bugs](), [compilation](), [engineering](), [instrumentation](), [latency](), [llvm](), [meta](), [optimization](), [performance](), [profile](), [profiling]() ### AI overview This article describes how Redpanda optimized its binary for Redpanda Streaming 26.1 using compiler-based profile-guided optimization (PGO) and LLVM BOLT. It explains how profiling data guides optimization decisions, compares the two approaches, and reports lower latency and CPU usage for intensive workloads. ### Source excerpt A behind-the-scenes look into how we optimized performance and cut latency in Redpanda 26.1 with profile-guided optimization. ## From Dagger to Metro DevFeed: [From Dagger to Metro]() Original publisher: [Read original article]() Author: Andrius Semionovas Published: 2026-02-12T00:00:00Z Content type: article Language: en Sources: [Vinted]() Topics: [Dependency injection](), [Android](), [migration](), [Kotlin](), [Dagger](), [interoperability](), [Compiler](), [modules](), [Gradle]() Tags: [android](), [compatibility](), [compilation](), [dagger](), [dependency-injection](), [gradle](), [interoperability](), [kotlin](), [migration](), [modules]() ### AI overview Vinted's Android developers describe their migration from Dagger and related dependency-injection tools to Metro. The article covers their large, modular codebase, Anvil's maintenance status and K2 migration pressure, and Metro's interoperability with Dagger, Anvil, and kotlin-inject. ### Source excerpt Metro - modern and kotlin injection framework created by Zac Sweers. And we, Android developers at Vinted, officially and fully migrated to it! It was quite a bumpy ride for our huge codebase. Our story begins... ## \[RevEng\]\[x86\]\[x64\]\[C\]\[newbies\] Software reset in embedded devices DevFeed: [\[RevEng\]\[x86\]\[x64\]\[C\]\[newbies\] Software reset in embedded devices]() Original publisher: [Read original article]() Published: 2025-12-31T23:00:00Z Content type: tutorial Language: en Sources: [Dennis Yurichev]() Topics: [C](), [Embedded Software Dev](), [Code](), [x86](), [gcc]() Tags: [blog-post](), [c](), [code](), [compilation](), [embedded](), [embedded-devices](), [gcc](), [software](), [x86]() ### AI overview This tutorial explains a software-reset technique for embedded devices using pure C. It shows how calling a function pointer at address zero can jump to firmware on systems that start execution there after power-on or reset, and discusses the behavior of the stack and local variables. ### Source excerpt [RevEng][x86][x64][C][newbies] Software reset in embedded devices ## Cross-Compiling NixOS images DevFeed: [Cross-Compiling NixOS images]() Original publisher: [Read original article]() Author: Jacek Galowicz Published: 2025-12-20T00:00:00Z Content type: tutorial Language: en Sources: [Nixcademy Blog]() Topics: [Nix](), [Cross-Compilation](), [gnu linux](), [systemd]() Tags: [article](), [compilation](), [cross-compilation](), [how-to](), [learn](), [linux](), [systemd]() ### AI overview Part four of a series explaining how to cross-compile NixOS appliance images for other platforms while retaining Nix's declarative and composable configuration model. ### Source excerpt Part 4 of our NixOS appliance image series - Learn how to cross-compile NixOS images without losing declarativity and composability ## Integrating External Libraries into NuttX Applications DevFeed: [Integrating External Libraries into NuttX Applications]() Original publisher: [Read original article]() Author: John Lee Published: 2025-11-19T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [NuttX](), [Library](), [Simulation](), [ESP32-C6](), [RISC-V](), [x86]() Tags: [blog](), [compilation](), [cross-compilation](), [esp32-c6](), [guide](), [how-to](), [libraries](), [library](), [nuttx](), [practitioner](), [risc-v](), [simulation](), [x86]() ### AI overview This guide explains how to integrate an external application library into NuttX using a static library and cross-compilation. It covers building the library on x86, testing it in the NuttX simulation environment, and cross-compiling it for RISC-V to run on the ESP32-C6. ### Source excerpt This guide demonstrates how to integrate external libraries into NuttX applications using static libraries and cross-compilation. Learn how to build a library on x86, integrate it into the NuttX simulation environment, and cross-compile for RISC-V targets like the ESP32-C6, all without moving your entire codebase into the NuttX directory structure. ## Inside Go -- Part 1: The Compilation Pipeline DevFeed: [Inside Go -- Part 1: The Compilation Pipeline]() Original publisher: [Read original article]() Author: Furkan Kolcu Published: 2025-09-11T10:34:38Z Content type: tutorial Language: en Sources: [Furkan Kolcu - Software Engineer Blog]() Topics: [Go Language](), [Compiler](), [Parsing](), [Parser](), [Optimization](), [Code generation](), [Assembly]() Tags: [assembly](), [ast](), [code-generation](), [compilation](), [go](), [go-ast](), [go-compilation](), [go-compiler](), [go-internals](), [go-lexer](), [go-parser](), [go-ssa](), [golang](), [optimization](), [parsing](), [ssa](), [technology]() ### AI overview This tutorial explains how Go source code is transformed into a native executable. It covers lexing and parsing, abstract syntax trees, type checking, SSA, optimization, code generation, and linking, with simple examples and analogies. ### Source excerpt In this first part of the "Inside Go" series, I'll walk through how Go source code transforms into a binary. From lexing and parsing to ASTs, SSA, and optimizations, we'll explore the steps of the Go compilation pipeline with simple code examples and analogies to make sense of it all. ## Inside Go -- How It Really Works: Series Kickoff DevFeed: [Inside Go -- How It Really Works: Series Kickoff]() Original publisher: [Read original article]() Author: Furkan Kolcu Published: 2025-09-11T10:16:52Z Content type: article Language: en Sources: [Furkan Kolcu - Software Engineer Blog]() Topics: [Go Language](), [Compiler](), [Concurrency](), [Code](), [Optimization](), [escape analysis](), [generics](), [modules](), [reproducible builds]() Tags: [compilation](), [concurrency](), [deep-dive](), [generics](), [go](), [go-compiler](), [go-concurrency](), [go-performance](), [go-runtime](), [golang](), [how-go-works](), [inside-go](), [internals](), [memory-management](), [performance](), [technology]() ### AI overview This article launches a technical series about how Go works internally. The planned installments cover compilation, memory management, garbage collection, concurrency, the runtime, performance tuning, interfaces, generics, modules, and reproducible builds, with code examples and runtime experiments. ### Source excerpt A deep-dive series into Go's internals. From compilation to memory management, concurrency, and performance tuning, each part unpacks how Go operates under the hood with clear explanations and real-life code examples. ## Make your ZeroGPU Spaces go brrr with ahead-of-time compilation DevFeed: [Make your ZeroGPU Spaces go brrr with ahead-of-time compilation]() Original publisher: [Read original article]() Author: Charles Bensimon; Sayak Paul; Linoy Tsaban; Apolinário from multimodal AI art Published: 2025-09-02T00:00:00Z Content type: tutorial Language: en Sources: [Hugging Face - Blog]() Topics: [RAPIDS](), [GPU](), [fly](), [PyTorch](), [quantization](), [Open Source]() Tags: [compilation](), [gpu](), [guide](), [hugging-face](), [image-to-image](), [image-to-video](), [inference](), [latency](), [models](), [optimization](), [python](), [pytorch](), [quantization](), [spaces](), [text-to-image](), [zerogpu]() ### AI overview This tutorial explains how to use PyTorch ahead-of-time compilation in ZeroGPU Spaces. It covers faster model startup and inference, FP8 quantization, dynamic shapes, and the process-based GPU allocation model used by ZeroGPU, with reported speedups of 1.3x-1.8x on Flux, Wan, and LTX models. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Type-safe Project Accessors Can Trigger Broad Kotlin Gradle DSL Recompilation DevFeed: [Type-safe Project Accessors Can Trigger Broad Kotlin Gradle DSL Recompilation]() Original publisher: [Read original article]() Author: Zac Sweers Published: 2025-07-02T02:00:33Z Content type: opinion Language: en Sources: [Zac Sweers]() Topics: [Gradle](), [Kotlin](), [Caching]() Tags: [cache](), [compilation](), [developer-experience](), [gradle](), [kotlin]() ### AI overview The article argues that Gradle type-safe project accessors can cause broad recompilation in Kotlin Gradle DSL builds. Changes to included projects alter generated accessor ABIs, potentially invalidating build-script and compilation caches, especially in larger codebases and workflows that minimize included projects. ### Source excerpt Another Gradle footgun ## Introducing Metro, a Kotlin compiler-plugin dependency injection framework DevFeed: [Introducing Metro, a Kotlin compiler-plugin dependency injection framework]() Original publisher: [Read original article]() Author: Zac Sweers Published: 2025-04-03T16:14:23Z Content type: article Language: en Sources: [Zac Sweers]() Topics: [Dependency injection](), [Compiler](), [Kotlin](), [multiplatform](), [build performance](), [benchmarking]() Tags: [anvil](), [benchmarking](), [build-performance](), [compilation](), [compiler](), [dagger](), [dependency-injection](), [error-messages](), [kotlin](), [metro](), [multiplatform]() ### AI overview The article introduces Metro, a Kotlin compiler-plugin framework for compile-time dependency injection. It combines ideas from Dagger, Anvil, and Kotlin-Inject, and describes features including dependency graph validation, code generation, multiplatform support, IDE integration, and diagnostics. The author reports benchmarked build-time improvements in a CatchUp app and notes that Metro 0.1.1 is in active development. ### Source excerpt I'm excited to share something new I've been working on the past few months! ## Next.js 15.2 DevFeed: [Next.js 15.2]() Original publisher: [Read original article]() Author: Zack Tanner Published: 2025-02-26T20:00:00Z Content type: release Language: en Sources: [Next.js Blog]() Topics: [Next.js](), [debugging](), [React](), [Streaming](), [view transitions](), [Node.js]() Tags: [compilation](), [debugging](), [errors](), [memory](), [next-js](), [node-js](), [performance](), [react](), [streaming](), [updates](), [view-transitions]() ### AI overview Next.js 15.2 introduces a redesigned error interface with improved stack traces, asynchronous streaming metadata, Turbopack performance improvements, experimental React View Transitions support, and experimental Node.js Middleware runtime support. ### Source excerpt Next.js 15.2 includes updates for debugging errors, metadata, Turbopack, and more. 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