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Clean Code

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  1. 1
    Microsoft Word gets open-source clean-room reimplementation in Rust▼An open-source, clean-room reimplementation of Microsoft Word in pure RustYhnEnvironmentWeather1019 h ago

    A project called Wordcraft, hosted on GitHub, is presenting itself as a clean-room reimplementation of Microsoft Word written entirely in Rust. Clean-room development means the software is built from published documentation rather than the original code, aiming to avoid copyright issues while reproducing Word's functionality. The project is drawing attention among developers interested in Rust and in open alternatives to commercial office software.

  2. 2
    Clean room reimplementation of Adobe products emerges▼Clean room implementation of Adobe productsYhnSportCricket261 d ago

    A developer has released a clean room implementation of Adobe products, rebuilding compatible software from scratch without using Adobe's proprietary code. The project, hosted on GitHub under the account storytold, is drawing attention among developers interested in open-source alternatives to Adobe's creative suite. Discussion is focused on the technical challenge and the legal safety of clean room reverse engineering practices.

  3. 3
    Deslop: new lint rules target AI-generated TypeScript code●Show HN: Deslop – Oxlint rules for AI-generated TypeScriptYhnSportCricket281 d ago

    A developer has released Deslop, a set of Oxlint rules designed to flag common patterns and low-quality code produced by AI coding assistants in TypeScript projects. The tool is open source on GitHub and was shared with the Hacker News community, where it is drawing attention from developers interested in cleaning up machine-written code.

  4. 4
    Robert C. Martin criticised for pivot from Clean Code to AI●Oh! "Creepy Uncle Bob" (Robert C. Martin) has completely ditched his "Clean Code" grift and fully pivoted to AI! 🫠 # cleMmastodonTechnologySoftware1272 d ago

    Software community commentary targets Robert C. Martin, known for the influential Clean Code books, claiming he has abandoned his software craftsmanship focus and rebranded himself around artificial intelligence. Critics in programming circles mock the shift, with some calling his Clean Code teachings a grift and tying the move to broader frustration with AI hype in development.

  5. 5
    Developer releases Spool to manage persistent Claude Code loops●How I manage persistent Claude Code loops: SpoolYhn78 h ago

    A developer has released Spool, an open-source tool for managing persistent loops in Claude Code, Anthropic's AI coding assistant. The tool, available on GitHub, is drawing attention from developers who run long automated coding sessions and struggle with sessions that repeat tasks or fail to terminate cleanly.

  6. 6
    Warning against keeping your working code on free remote coding servers●You should never place your everyday working tree on a free remote coding server, because that tree is a suitcase, not aMmastodonTechnologyAI46 d ago

    Developers are being warned not to keep their everyday working code directory on free remote coding servers. The argument: such a working tree is like a suitcase, not a clean source drop — underneath the chat interface it still carries git remotes, ignored files and local notes that can be exposed. The advice is to treat remote servers as disposable, keeping sensitive and active work on your own machine.

  7. 7
    Google Translate may gain Gboard-style Rambler speech cleanup▼Google Translate could soon get its own version of Gboard’s Rambler Smart assist would clean up your messy speech beforeMmastodonBusinessStartups14 d ago

    Google Translate could soon add a feature similar to Gboard's Rambler Smart assist, which tidies up rambling or messy spoken input before it is translated. The idea is that cleaner speech would produce more accurate translations. Details appear to come from early findings in the app, and Google has not confirmed anything, so timing and availability remain unknown.

  8. 8
    Why most tech resumes fail ATS parsers●As software engineers, we obsess over deterministic logic, zero-downtime deployments, and clean... # career # webdev # aMmastodonTechnologyAI35 d ago

    Software engineers are discussing why the majority of tech resumes get rejected by corporate applicant tracking systems before a human ever reads them. The conversation contrasts the industry's obsession with deterministic logic, clean code and zero-downtime deployments with the irony that engineers' own job applications are routinely filtered out by rigid parsing software, with advice circulating on formatting and keyword choices.

  9. 9
    AI-built Rust clones of Photoshop and Premiere emerge▼AI Makes "Open-Source, Clean Room" Implementations Of Adobe Photoshop & Premier In Rust✉newsTechnologySoftware6 d ago

    New open-source, clean room implementations of Adobe Photoshop and Premiere, written in Rust with help from AI, are drawing attention in the Linux and developer communities. The projects aim to recreate Adobe's creative tools without using proprietary code, offering free alternatives to Photoshop and Premiere that could run natively on Linux.

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    Clean chatbot transcripts are not code review records, developer warns●A clean transcript is not a review record. I want a local receipt before any free session touches my branch. If that recMmastodonTechnologyAI25 d ago

    A developer is pushing back on treating an AI chat transcript as proof that code was reviewed, arguing that summaries can outrun the actual diff. They want a local receipt generated before any free session touches their branch, and refuse to share work if that receipt is empty. A confident final reply from the assistant, they say, does not count as verification.

  11. 11
    New Code Review Checklist Targets AI Coding Agents●AI coding agents write fluent, syntactically clean code that compiles on the first attempt. That... # productivity # proMmastodonTechnologySoftware46 d ago

    A new five-axis code review checklist is being shared for teams working with AI coding agents. The argument: these agents produce fluent, syntactically clean code that compiles on the first attempt, but surface-level quality can hide deeper design and correctness problems. The checklist aims to give reviewers a structured way to assess AI-generated code beyond whether it simply builds and runs.

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