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
大規模言語モデル (LLM) の学習データに含まれない知識（各社の特有の書類など）を踏まえてLLMに回答させる際に最早必須となってきたRAG (Retrieval-Augumented Generation)。 今回はそんなRAGのSurvey論文を元に、RAGの変遷や構成要素、新たに出てきた技術を俯瞰していきます。 Survey論文へのリンクはこちら arxiv.org RAGとは LLMはそれ単体で回答させると、質問によってはハルシネーションや学習時のデータにはなかった情報を生成時に加味できないといった問題から正しくない回答を生成することが多々あります。例えば世間一般に公開されていない自社の就業規則や業務標準についてをChatGPTに質問しても、正しい回答は得られません。 そのような問題への対応としてRAGが使われます。 「LLM単体で適切な回答を生成できないなら、ユーザーの質問を元に
今年も GitHub トレンドから 2022 年の JavaScript/TypeScript を振り返ります。去年の記事はこちらです。 — GitHub のトレンドで振り返る 2021 年の JavaScript | WEB EGG 集計方法 本記事の集計期間は 2022/01/01〜2022/12/07、対象言語は JavaScript および TypeScript です。 なお GitHub がそのリポジトリをなんの言語と見なしてトレンドに掲載したかをもとに集計対象を決定していることにご留意ください。 別言語で書かれた Rust 製の JS 向けのツールや CSS フレームワークなどは基本的に対象外となります。 集計に利用したデータですが、GitHub は過去のトレンドを閲覧する方法を提供していないため、独自の仕組みで GitHub トレンドのアーカイブを生成しそのデータを利用しまし
llm-wiki
llm-wiki.md LLM Wiki A pattern for building personal knowledge bases using LLMs. This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you. The core idea Most people's experience with LLMs and documents lo
Go Scheduler
Go Scheduler Contents Introduction Compilation and Go Runtime Primitive Scheduler Scheduler Enhancement GMP Model Program Bootstrap Creating a Goroutine Schedule Loop Finding a Runnable Goroutine Goroutine Preemption Handling System Calls Network I/O and File I/O How netpoll Works Garbage Collector Common Functions Go Runtime APIs Disclaimer This blog post primarily focuses on Go 1.24 programming
AI agents didn't make the SDLC faster. They killed it. I keep hearing people talk about AI as a "10x developer tool." That framing is wrong. It assumes the workflow stays the same and the speed goes up. That's not what's happening. The entire lifecycle, the one we've built careers around, the one that spawned a multi-billion dollar tooling industry, is collapsing in on itself. And most people have
How the Open Knowledge Format can improve data sharing | Google Cloud Blog
Amir HormatiTech Lead, BigQuery, Engineering, Data Cloud As foundation models continue to improve, the lack of relevant context often limits what they can do, especially as they are used to build agentic systems. While these models can help you write code, summarize documents, or analyze a dataset, they still need the right information to produce accurate and actionable results. That’s why today,
何年後かの自分へ こんにちは、のんピ(@non____97)です。 業務で使用する新しいMacが届きました。 新しいMacを初期セットアップするにあたって「今の設定どうだったっけ...」と調べる時間が結構かかってしまいました ということで何年後かの自分がまた新しいMacに乗り換える際に手間取らないように、設定した内容を書き記しておきます。 移行先のMacの情報は以下の通りです。M1 Max、嬉しい。 # OSのバージョンの確認 > sw_vers ProductName: macOS ProductVersion: 12.4 BuildVersion: 21F79 # カーネルのバージョン確認 > uname -r 21.5.0 # CPUのアーキテクチャの確認 > uname -m arm64 # CPUの詳細確認 > sysctl -a machdep.cpu machdep.cpu.
GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
Official integrations are maintained by companies building production ready MCP servers for their platforms. 21st.dev Magic - Create crafted UI components inspired by the best 21st.dev design engineers. 2slides - An MCP server that provides tools to convert content into slides/PPT/presentation or generate slides/PPT/presentation with user intention. ActionKit by Paragon - Connect to 130+ SaaS inte
keyv 等 複数著名パッケージへのソフトウェアサプライチェーン攻撃の概要と対応指針 - GMO Flatt Security Blog
2026年8月4日、npm ユーザー jaredwray が管理に関与する、複数の npm パッケージに悪性コードが注入されました。 一部は週間で一億回以上ダウンロードされている、広く利用されているパッケージです。 注入された悪性コードは Infostealer 型マルウェアです。Lifecycle script 経由で開発者のもつ認証情報を盗み出し、C2 へ送出します。 また、環境に存在するトークンによっては、他 npm パッケージに悪性コードを植え付け侵害するワーム性も持ちます。 本記事は、弊社が Takumi Guard の解析基盤をベースに観測＆分析した情報を踏まえ、 日本のコミュニティに向けて、影響と対策を中心に整理するものです。 TL;DR — 対応指針 はじめに 侵害の仕組み Stage 0 — 悪性パッケージの発火 Stage 1 — Bun ランタイムのダウンロードと実行
awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems View the Project on GitHub View On GitHub An updated and organized reading list for illustrating the patterns of scalable, reliable, and performant large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to
This all started with a blog post back in 2020, from a tech curiosity: what's the fastest way to scale containers on AWS? Is ECS faster than EKS? What about Fargate? Is there a difference between ECS on Fargate and EKS on Fargate? I had to know this to build better architectures for my clients. In 2021, containers got even better, and I was lucky enough to get a preview and present just how fast t
GitHub - colbymchenry/codegraph: Pre-indexed code knowledge graph for Claude Code, Codex, Gemini, Cursor, OpenCode, AntiGravity, Kiro, and Hermes Agent — fewer tokens, fewer tool calls, 100% local
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GitHub - antirez/ds4: DeepSeek 4 Flash local inference engine for Metal and CUDA
DrawfStar 4 is a small native inference engine specific for DeepSeek V4 Flash. It is intentionally narrow: not a generic GGUF runner, not a wrapper around another runtime: it is completely self-contained. Other than running the model in a correct and fast way, the project goal is to provide DS4 specific loading, prompt rendering, tool calling, KV state handling (RAM and on-disk), and server API, a
How the Open Knowledge Format can improve data sharing | Google Cloud Blog
Amir HormatiTech Lead, BigQuery, Engineering, Data Cloud As foundation models continue to improve, the lack of relevant context often limits what they can do, especially as they are used to build agentic systems. While these models can help you write code, summarize documents, or analyze a dataset, they still need the right information to produce accurate and actionable results. That’s why today,
We are sharing the first complete computer-checked proof of Fermat’s Last Theorem. Claude worked largely autonomously over 11 days to write the proof in the Lean programming language. Below, we describe how the formalization was done and share some thoughts about what this work could mean for research mathematics. Around 1637, Pierre de Fermat jotted down a claim in the margin of his copy of Dioph
The Factory Model: How Coding Agents Changed Software Engineering | AddyOsmani.com
The Factory Model: How Coding Agents Changed Software Engineering February 25, 2026 Something shifted recently with agentic engineering that “feels” like the level of abstraction changed again. Not the usual kind of shift where tools get marginally better and workflows gradually evolve. A step change. Developers who have been writing software for decades are describing it the same way: the center
Welcome to the very first post in a new blog! Here I will discuss software development, SRE work, and other fun stuff. Sometimes an idea is just too good to pass up. I hope this blog will motivate me to turn sparks and little pieces into general knowledge in writing the words down. The other day I was discussing Tabby with a coworker. We talked about whether we should consider AI-autocompleted cod
Hypershell: A Type-Level DSL for Shell-Scripting in Rust | Context-Generic Programming
Discuss on Reddit, Lobsters, and Hacker News. Summary I am thrilled to introduce Hypershell, a modular, type-level domain-specific language (DSL) for writing shell-script-like programs in Rust. Hypershell is powered by context-generic programming (CGP), which makes it possible for users to extend or modify both the language syntax and semantics. Table of Contents Estimated reading time: 1~2 hours
GitHub - punkpeye/awesome-mcp-servers: A collection of MCP servers.
Servers for accessing many apps and tools through a single MCP server. 1mcp/agent 📇 ☁️ 🏠 🍎 🪟 🐧 - A unified Model Context Protocol server implementation that aggregates multiple MCP servers into one. tadas-github/a2asearch-mcp 📇 ☁️ - MCP server to search 4,800+ MCP servers, AI agents, CLI tools and agent skills. Install: npx -y a2asearch-mcp. Ask Claude: "Find MCP servers for database access"
Biome v2—codename: Biotype
We are happy to announce that Biome v2 is officially out! 🍾 Biome v2—codename: Biotype, the first JavaScript and TypeScript linter that provides type-aware linting rules that doesn’t rely on the TypeScript compiler! This means that you can lint your project without necessarily installing the typescript package. With this release, the Core Contributors of the project want to show to the whole comm
Notes by djb on using Fil-C (2025) I'm impressed with the level of compatibility of the new memory-safe C/C++ compiler Fil-C (filcc, fil++). Many libraries and applications that I've tried work under Fil-C without changes, and the exceptions haven't been hard to get working. I've accumulated miscellaneous notes on this page regarding usage of Fil-C. My selfish objective here is to protect various
Strands Agents の50個の標準ツールを一挙紹介 〜AIエージェントをより便利にするツール群〜 - Taste of Tech Topics
こんにちは、前田です。 最近、社内で「城巡り同好会」を立ち上げ、小田原城に行ってきました。 天守閣からは相模湾と箱根の山々が連なる絶景を見られて、とても良かったです。 さて、今回はAIエージェント開発には欠かせないライブラリ 「Strands Agents」 の標準ツールを紹介します。 1. Strands Agentsとは 1.1. まずは動かしてみる 2. 標準ツール紹介 2.1. ファイル操作 2.2. 自動化 2.3. 情報収集 2.4. マルチメディア 2.5. エージェント 2.6. その他 3. 実践：AWSコスト分析エージェント 3.1. 何をするエージェントか 3.2. コード 3.3. 実行結果 1. Strands Agentsとは Strands AgentsはAWSがオープンソースとして公開したAIエージェント開発用のSDKです。 aws.amazon.com A
I’m happy to announce the release of Box3D, an open source 3D physics engine. It is now available on GitHub. Box3D repository You can think of Box3D as a fork of Box2D, extended with many features needed for 3D games. Some additions: Triangle mesh collision Height-field collision Baked compound collision The core architecture of Box3D remains almost identical to Box2D. C API All library source is
GitHub - Egonex-AI/Understand-Anything: Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
Turn any codebase, knowledge base, or docs into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more. Understand Anything. Understand Anyone. AI should help people, not replace them. English | 简体中文 | 繁體中文 | 日本語 | 한국어 | Español | Türkçe | Русский An open-source project from Egonex Originally created by
microgpt
This is a brief guide to my new art project microgpt, a single file of 200 lines of pure Python with no dependencies that trains and inferences a GPT. This file contains the full algorithmic content of what is needed: dataset of documents, tokenizer, autograd engine, a GPT-2-like neural network architecture, the Adam optimizer, training loop, and inference loop. Everything else is just efficiency.
Effective TypeScript › Flow Nodes: How Type Inference Is Implemented
In most programming languages a variable has a type and that type does not change. But one of the most interesting aspects of TypeScript's type system is that a symbol has a type at a location. Various control flow constructs can change this type: function refine(x: string | number) { // type of x is string | number here if (typeof x === 'number') { // type of x is number here. } else { // type of
We’re excited to announce the release of Biome 2.3, bringing several features that have been highly requested by the community. This release marks a significant milestone in our journey to support the broader web ecosystem. Once you have upgraded to Biome v2.3.0, migrate your Biome configuration to the new version by running the migrate command: biome migrate --write Full support for Vue, Svelte,
January 10, 2025 This article was contributed by Murukesh Mohanan The death of Bram Moolenaar, Vim founder and benevolent dictator for life (BDFL), in 2023 sent a shock through the community, and raised concern about the future of the project. At VimConf 2024 in November, current Vim maintainer Christian Brabandt delivered a keynote on "the new Vim project" that detailed how the community has reor
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
Rust is an appealing language for building user interfaces for a variety of reasons, especially the promise of delivering both performance and safety. However, finding a good architecture is challenging. Architectures that work well in other languages generally don’t adapt well to Rust, mostly because they rely on shared mutable state and that is not idiomatic Rust, to put it mildly. It is sometim
MemLab: An open source framework for finding JavaScript memory leaks
MemLab: An open source framework for finding JavaScript memory leaks We’ve open-sourced MemLab, a JavaScript memory testing framework that automates memory leak detection. Finding and addressing the root cause of memory leaks is important for delivering a quality user experience on web applications. MemLab has helped engineers and developers at Meta improve user experience and make significant imp
knowledge-catalog/okf at main · GoogleCloudPlatform/knowledge-catalog
Important OKF now lives in its own repository: GoogleCloudPlatform/open-knowledge-format. That repository is the canonical home of the specification, the reference agent, and the sample bundles. Please read the spec, file issues, and open pull requests there. Stop using the copy under okf/ in this repository. It is a frozen snapshot, no longer maintained, and anything built against it will drift o
Our Experience Porting the YJIT Ruby Compiler to Rust - Shopify
Our Experience Porting the YJIT Ruby Compiler to RustIn this post, I want to give a nuanced perspective on our experience porting YJIT from C to Rust. I'll talk about the positives, but also discuss the things that we found challenging or suboptimal in our experience. Last year, my team at Shopify implemented YJIT, a new Just-In-Time (JIT) compiler for CRuby, which was recently upstreamed as part
GitHub - confident-ai/deepeval: The LLM Evaluation Framework
📐 Large variety of ready-to-use LLM eval metrics (all with explanations) powered by ANY LLM of your choice, statistical methods, or NLP models that run locally on your machine covering all use cases: Custom, All-Purpose Metrics: G-Eval — a research-backed LLM-as-a-judge metric for evaluating on any custom criteria with human-like accuracy DAG — DeepEval's graph-based deterministic LLM-as-a-judge
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
Did you know that macOS has a secret setting that can make Rust builds faster? It can also make Rust tests faster (sometimes massively so). It probably even has similar effects for other compiled languages such as C, C++, Go, and Swift. It sounds crazy, but read on… The problem Isaac Asimov reportedly said: the most exciting phrase to hear in science… is not “Eureka” but “that’s funny…” I noticed
Questionable Advice: “My boss says we don’t need any engineering managers. Is he right?”
I recently joined a startup to run an engineering org of about 40 engineers. My title is VP Engineering. However, I have been having lots of ongoing conflict with the CEO (a former engineer) around whether or not I am allowed to have or hire any dedicated engineering managers. Right now, the engineers are clustered into small teams of 3-4, each of which has a lead engineer — someone who leads the
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.”
Recently I landed experimental support for require()-ing synchronous ES modules in Node.js, a feature that has been long overdue. In the pull request, I commented with my understanding about why it did not happen sooner before this pull request in 2024. This post expands on that comment a bit more. The opinions in this post are my own and reflect my perception of the ESM development in Node.js as
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RAGのSurvey論文からRAG関連技術を俯瞰する - 元生技のデータサイエンティストのメモ帳
GitHubのトレンドで振り返る2022年のJavaScript/TypeScript
The Software Development Lifecycle Is Dead | Boris Tane
ぼくのMac環境 ver.のんピ | DevelopersIO
Scaling containers on AWS in 2022
Formalizing Fermat's Last Theorem
Test-Driven Development with an LLM for Fun and Profit
Notes by djb on using Fil-C (2025)
Announcing Box3D :: Box2D
Biome v2.3—Let's bring the ecosystem closer
The state of Vim
Xilem: an architecture for UI in Rust
Kalyn: a self-hosting compiler for x86-64
Faster Rust builds on Mac
Patterns for Building LLM-based Systems & Products
require(esm) in Node.js