SShortSingh.
Back to feed

Developer turns forgotten 2005 HCI research into a Chrome extension for easier clicking

0
·1 views

A developer has built a Chrome extension called MagPoint, inspired by a 2005 academic paper by Grossman and Balakrishnan titled 'The Bubble Cursor,' which proposed making cursor hit areas dynamic to always target the nearest clickable element. The original research demonstrated significant speed improvements in controlled experiments but was never implemented in mainstream browsers or operating systems. MagPoint works by calculating the closest clickable element to the pointer each frame and rerouting nearby clicks toward it, while disengaging beyond a 120-pixel radius to preserve normal behavior in empty space. The extension also pauses its magnetic behavior during text input to avoid interfering with typing. The developer published the source code along with an automated demo-recording pipeline using headless Chromium and scripted cursor paths.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingHacker News ·

PostgreSQL May Replace Multiple Specialized Systems in Your Stack

A discussion on Hacker News highlights a growing perspective that PostgreSQL alone can handle many infrastructure needs typically split across multiple systems. The argument centers on Postgres's broad feature set, which includes support for queuing, search, caching, and more. Developers are questioning whether adding separate specialized tools is always justified when Postgres already covers those use cases. The conversation is linked to a dedicated site, postgresisenough.dev, making the case for consolidating around a single database. The post has attracted community engagement on Hacker News, sparking debate about simplicity versus specialization in modern software stacks.

0
ProgrammingDEV Community ·

MongoDB vs PostgreSQL: A Practical Guide to Picking the Right Database in 2026

PostgreSQL and MongoDB are both mature, production-ready databases suited to different use cases rather than competing on quality. PostgreSQL is a relational database that enforces strict schemas, supports complex joins, and offers strong ACID transaction guarantees, making it ideal for financial systems, e-commerce, and SaaS platforms. MongoDB is a document-based NoSQL database that stores flexible JSON-like records, making it a natural fit for rapidly evolving data models, content management, and high-throughput applications. The key deciding factor is the shape of your data: highly relational, structured data favors PostgreSQL, while fluid, document-shaped, or object-driven data favors MongoDB. Developers are advised to treat the choice as a practical one based on data structure and access patterns rather than a high-stakes debate.