Google LLC’s presence in the developer community can be felt far beyond the Android ecosystem. The search giant is responsible for TensorFlow, numerous cybersecurity tools and Flutter, the popular open-sourcing framework for building apps that work on multiple platforms.

Google today launched a new version of Flutter along with an update to the Dart programming language the framework uses. The releases advance the project’s goal of fostering interoperable software by adding support for more platforms, as well as improving support for the ones it already works with.

Flutter 1.9 introduces compatibility with Apple Inc.’s upcoming macOS Catalina and iOS 13 operating system releases. Google has furthermore introduced the ability to write apps for the web, which fills in another key piece of the interoperability puzzle. It means that developers can now use Flutter to create software that runs on Windows, macOS, Linux, Android, iOS and in browsers without having to create separate editions for each platform.

Google also took the time to add support for some of the unique features in each operating system. On macOS Catalina, Flutter supports Xcode 11, the latest version of Apple’s coding toolkit. On iOS 13, the framework enables developers to make use of the new drag feature that lets users scroll through content faster by pulling the page up or down.

Flutter 1.9 is rolling out alongside the enhanced Dart 2.5 programming language. Dart was developed internally by Google and closely resembles Java in syntax, though it serves a much different purpose.

There are two tent pole enhancements in the new release. The first is Dart-C, a mechanism that continues the theme of improved cross-platform support by enabling Dart applications to more efficiently interact with operating system components written in the C language. The feature will be a big aid to developers building applications for Linux, which is largely based on C.

Dart-C also allows Dart programs to better access the countless other foundational software tools written in C, such as the SQLite mobile database and Google’s own TensorFlow artificial intelligence tool.

Capping off the enhancements is an experimental feature called ML Complete. It uses a TensorFlow-powered artificial intelligence model to detect when a developer starts typing code and display relevant completion suggestions. If an engineer is working on an application component that tells the time, for instance, ML Complete can highlight compatible clock libraries. 

Photo: Google