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  • 関数名、メソッド名、変数名でよく使う英単語のまとめ

    プログラミングをしていると関数名、メソッド名、変数名をどうするか悩みます。 ロジックより命名に時間を費やすこともざらにあります。翻訳したり、一般的な命名規則なのかいつも検索して大変です。 よく使うサイトの内容をコピってメモしておく 関数名とメソッド名の違いについて よく使う英単語のまえに、いつもごっちゃにして使っているけど、定義はこんな感じ 「関数」と「メソッド」の違い 似ているところ どちらも何か(引数)を入れると処理をして何か(戻り値)を返してくれます。 違うところ やってること自体は大差ありません。概念としては違います。 メソッドはオブジェクト指向で登場する用語で、オブジェクトの動作を定義したものです。 まずオブジェクトありきなのですね。一方の関数は、オブジェクト云々は関係ありません。 個人的な使い分け Java で登場する関数は「メソッド」です。C 言語で登場する関数は「関数」と呼

      関数名、メソッド名、変数名でよく使う英単語のまとめ
    • research!rsc: Coroutines for Go

      This post is about why we need a coroutine package for Go, and what it would look like. But first, what are coroutines? Every programmer today is familiar with function calls (subroutines): F calls G, which stops F and runs G. G does its work, potentially calling and waiting for other functions, and eventually returns. When G returns, G is gone and F continues running. In this pattern, only one fu

      • Weird Lexical Syntax

        I just learned 42 programming languages this month to build a new syntax highlighter for llamafile. I feel like I'm up to my eyeballs in programming languages right now. Now that it's halloween, I thought I'd share some of the spookiest most surprising syntax I've seen. The languages I decided to support are Ada, Assembly, BASIC, C, C#, C++, COBOL, CSS, D, FORTH, FORTRAN, Go, Haskell, HTML, Java,

          Weird Lexical Syntax
        • AST vs. Bytecode: Interpreters in the Age of Meta-Compilation

          233 AST vs. Bytecode: Interpreters in the Age of Meta-Compilation OCTAVE LAROSE, University of Kent, UK SOPHIE KALEBA, University of Kent, UK HUMPHREY BURCHELL, University of Kent, UK STEFAN MARR, University of Kent, UK Thanks to partial evaluation and meta-tracing, it became practical to build language implementations that reach state-of-the-art peak performance by implementing only an interprete

          • Implementing Logic Programming

            Most of my readers are probably familiar with procedural programming, object-oriented programming (OOP), and functional programming (FP). The majority of top programming languages on all of the language popularity charts (like TIOBE) support all three to some extent. Even if a programmer avoided one or more of those three paradigms like the plague, they’re likely at least aware of them and what th

              Implementing Logic Programming
            • Kalyn: a self-hosting compiler for x86-64

              Over the course of my Spring 2020 semester at Harvey Mudd College, I developed a self-hosting compiler entirely from scratch. This article walks through many interesting parts of the project. It’s laid out so you can just read from beginning to end, but if you’re more interested in a particular topic, feel free to jump there. Or, take a look at the project on GitHub. Table of contents What the pro

              • Patterns for Building LLM-based Systems & Products

                Patterns for Building LLM-based Systems & Products [ llm engineering production 🔥 ] · 66 min read Discussions on HackerNews, Twitter, and LinkedIn “There is a large class of problems that are easy to imagine and build demos for, but extremely hard to make products out of. For example, self-driving: It’s easy to demo a car self-driving around a block, but making it into a product takes a decade.”

                  Patterns for Building LLM-based Systems & Products
                • Migrating from Go to Rust | corrode Rust Consulting

                  Out of all the migrations I help teams with, Go to Rust is a bit of an outlier. It’s not a question of “is Rust faster?” or “does Rust have types?”, Go already gets you most of the way there. The discussion is mostly about correctness guarantees, runtime tradeoffs, and developer ergonomics. A quick disclaimer before we start: this guide is heavily backend-focused. Backend services are where Go is

                    Migrating from Go to Rust | corrode Rust Consulting
                  • Solving Quantitative Reasoning Problems With Language Models

                    Solving Quantitative Reasoning Problems with Language Models Aitor Lewkowycz∗, Anders Andreassen†, David Dohan†, Ethan Dyer†, Henryk Michalewski†, Vinay Ramasesh†, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur∗, Guy Gur-Ari∗, and Vedant Misra∗ Google Research Abstract Language models have achieved remarkable performance on a wide range of tasks that require

                    • MAI-Thinking-1: Building a Hill-Climbing Machine

                      MAI-Thinking-1: Building a Hill-Climbing Machine The Microsoft AI Team 1 Abstract Progress in AI is driven not by a single model, but by the ability to continually improve upon the current state of models. Achieving this requires treating model development as a system-level optimization problem, for which the solution is building a hill-climbing machine for rapid improvement. Our process includes

                      • A Lisp Interpreter Implemented in Conway’s Game of Life

                        Lisp in Life is a Lisp interpreter implemented in Conway’s Game of Life. The entire pattern is viewable on the browser here. To the best of my knowledge, this is the first time a high-level programming language was interpreted in Conway’s Game of Life. Running Lisp on the Game of Life Lisp is a language with a simple and elegant design, having an extensive ability to express sophisticated ideas as

                          A Lisp Interpreter Implemented in Conway’s Game of Life
                        • The State of React and the Community in 2025

                          Random musings on React, Redux, and more, by Redux maintainer Mark "acemarke" Erikson Detailed thoughts on how React has been developed over time, and explanations for common community confusion and concerns Introduction 🔗︎ Today, the state of React and its ecosystem is complicated and fractured, with a mixture of successes, skepticism, and contention. On the positive side: React is the most wide

                            The State of React and the Community in 2025
                          • October 2025 (version 1.106)

                            Release date: November 12, 2025 Update 1.106.1: The update addresses these issues Update 1.106.2: The update addresses these issues Update 1.106.3: The update addresses these issues Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the October 2025 release of Visual Studio Code. This release brings significant updates across three key areas:

                              October 2025 (version 1.106)
                            • Type Parameters Proposal

                              Ian Lance Taylor Robert Griesemer August 20, 2021 StatusThis is the design for adding generic programming using type parameters to the Go language. This design has been proposed and accepted as a future language change. We currently expect that this change will be available in the Go 1.18 release in early 2022. AbstractWe suggest extending the Go language to add optional type parameters to type an

                              • Tech Solvency: The Story So Far: CVE-2021-44228 (Log4Shell log4j vulnerability).

                                Log4Shell log4j vulnerability (CVE-2021-44228 / CVE-2021-45046) - cheat-sheet reference guide Last updated: $Date: 2022/02/08 23:26:16 $ UTC - best effort, validate all for your environment/model before use, unofficial sources may be wrong by @TychoTithonus (Royce Williams), standing on the shoulders of many giants Send updates or suggestions (please include category / context / public (or support

                                • NumPy 2.0.0 Release Notes — NumPy v2.5.dev0 Manual

                                  Getting started What is NumPy? Installation NumPy quickstart NumPy: the absolute basics for beginners Fundamentals and usage NumPy fundamentals NumPy for MATLAB users NumPy tutorials NumPy how-tos Advanced usage and interoperability Using NumPy C-API F2PY user guide and reference manual Under-the-hood documentation for developers Interoperability with NumPy Extras Glossary Release notes 2.5.0 2.4.

                                  • What's New in Emacs 28.1?

                                    Try Mastering Emacs for free! Are you struggling with the basics? Have you mastered movement and editing yet? When you have read Mastering Emacs you will understand Emacs. It’s that time again: there’s a new major version of Emacs and, with it, a treasure trove of new features and changes. Notable features include the formal inclusion of native compilation, a technique that will greatly speed up y

                                    • A string formatting library in 65 lines of C++

                                      In this write-up, I will walk you through an implementation of a string formatting library for C++ I came up with for my video game. The end result came out really compact, at only 65 lines of code—providing a skeleton that can be supplemented with additional functionality at low cost. Usage Given a format buffer… char buffer[64]; String_Buffer buf = {str, sizeof str}; …the fmt::format function pr

                                      • Context Engineering - Short-Term Memory Management with Sessions from OpenAI Agents SDK

                                        Prerequisites Before running this cookbook, you must set up the following accounts and complete a few setup actions. These prerequisites are essential to interact with the APIs used in this project. Step0: OpenAI Account and OPENAI_API_KEY Purpose: You need an OpenAI account to access language models and use the Agents SDK featured in this cookbook. Action: Sign up for an OpenAI account if you don

                                          Context Engineering - Short-Term Memory Management with Sessions from OpenAI Agents SDK
                                        • std::flip

                                          std::flip is a little-known utility from the C++ standard library header <functional>: it is a higher-order function that accepts a Callable and returns an equivalent Callable with the order of its parameters reversed (or “flipped”). To understand how it can be useful, let’s start with a simple example. Consider the following tree node class: struct node { int value; node* parent = nullptr; node*

                                          • JavaScript Interview Questions

                                            Here is a list of common JavaScript interview questions with detailed answers to help you prepare for the interview as a JavaScript developer. JavaScript continues to be a cornerstone of web development, powering dynamic and interactive experiences across the web. As the language evolves, so does the complexity and scope of interview questions for JavaScript developers. Whether you’re a fresher de

                                              JavaScript Interview Questions
                                            • HTML Whitespace is Broken - Devel without a Cause

                                              HTML Whitespace is Broken September 2, 2024Recently, I was working on a project which required a deeper understanding of how whitespace works in HTML. I was never a fan of HTML's whitespace behavior before as I've been burned by it a few times. But as I dug into it more deeply, I found myself discovering complex design issues that I wanted to explore in a blog post. This is partially to write down

                                                HTML Whitespace is Broken - Devel without a Cause
                                              • Do large language models understand us?

                                                DisclaimerThese are my own views, not necessarily those of my employer. SummaryLarge language models (LLMs) represent a major advance in artificial intelligence (AI), and in particular toward the goal of human-like artificial general intelligence (AGI). It’s sometimes claimed, though, that machine learning is “just statistics”, hence that progress in AI is illusory with regard to this grander ambi

                                                  Do large language models understand us?
                                                • Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

                                                  Published as a conference paper at ICLR 2026 AGENTIC CONTEXT ENGINEERING: EVOLVING CON- TEXTS FOR SELF-IMPROVING LANGUAGE MODELS Qizheng Zhang1∗ , Changran Hu2∗ , Shubhangi Upasani2 , Boyuan Ma2 , Fenglu Hong2 , Vamsidhar Kamanuru2 , Jay Rainton2 , Chen Wu2 , Mengmeng Ji2 , Hanchen Li3 , Urmish Thakker2 , James Zou1 , Kunle Olukotun1 1 Stanford University 2 SambaNova Systems, Inc. 3 UC Berkeley {q

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