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A developer spent roughly a day porting 37signals' Rust-based Campfire chat app to Kotlin using Claude Code, aiming to see how the JVM would compare in DHH's running benchmark table of language rewrites. On x86 hardware, the Kotlin port matched Rust's requests-per-second and sometimes exceeded it, despite Kotlin not appearing in the original comparison table.
F-Droid, the open-source Android app store, has released version 2.0 with a rebuilt interface using Google's Material Design and a full rewrite of the codebase in Kotlin. The update reorganizes navigation into three sections—Discover, Search, and My Apps—and overhauls search to include app descriptions, tags, and translated terms rather than tracking user behavior.
F-Droid, the open source Android app repository, has released its first major client update in a decade. Version 2.0 was rewritten in Kotlin Compose with a cleaner interface, expanded app categories, and description-based search across its thousands of listed apps.
F-Droid has launched version 2.0 of its official app after more than a year of development and 14 test releases. The update rebuilds the interface using Kotlin Compose and Material Design, reorganizing navigation into three sections—Discover, Search, and My Apps—to improve app browsing, search, and update management. The rollout to users will happen gradually over the coming weeks.
Cubacadabra's developers plan to rebuild the product's iOS, Android, and web clients as thin native shells that delegate application logic to shared Rust crates rather than reimplementing features separately in Swift, Kotlin, and JavaScript. The goal is to move business rules like form validation, save logic, and error handling into one Rust codebase that all three platforms call into, citing Litter's Rust-core approach with UniFFI bindings as a precedent.
Shopify announced it is reversing its 2020 decision to standardize on React Native, moving its mobile engineering back to fully native development using Swift for iOS and Kotlin for Android. The company says rapid improvements in AI coding models have erased the productivity cost of maintaining two native codebases, which was the main reason it adopted a cross-platform framework in the first place.