Skip to content
Tech News
← Back to articles

Incremental – A library for incremental computations

read original more articles
Why This Matters

Incremental introduces a powerful approach for building computations that adapt efficiently to changing data, which can significantly enhance performance in applications like spreadsheets, GUIs, and data synchronization. Its ability to update derived data seamlessly helps reduce computational overhead and improve user experience. This innovation is poised to impact a wide range of software systems that rely on dynamic data processing.

Key Takeaways

Incremental is a library that gives you a way of building complex computations that can update efficiently in response to their inputs changing, inspired by the work of Umut Acar et. al. on self-adjusting computations. Incremental can be useful in a number of applications, including:

Building large calculations (of the kind you might build into a spreadsheet) that can react efficiently to changing data.

Constructing views in GUI applications that can incorporate new data efficiently.

Computing derived data while guaranteeing that the derived data stays in sync with the source data, for instance filtering or inversing a mapping.

You can find detailed documentation of the library and how to use it in incremental/src/incremental_intf.ml. You can also find an informal introduction to the library in this blog post and this video.