binary visualization

Christopher Domas presents his Cantor Dust tool at Derbycon 2012, a 3D visual approach to reverse engineering binaries by visualizing their structure dynamically.

Bret Victor's talk on Drawing Dynamic Visualizations. It argues that visualization tools offer either the directness of hand drawing or the dynamics of programmed graphics, and shows a tool that combines both.

Andrew Kelley's Zig SHOWTIME talk on an experiment to ship static Linux executables that can do graphics and gaming, followed by an interview. It covers the problems of Linux binary stability, dynamic linking and the graphics ABI.

Philip Roberts explains the JavaScript event loop, call stack, callbacks and asynchronous behavior with live visualizations using a tool he built. It demystifies terms like non-blocking and single-threaded.

A Google Tech Talk by Laurens van der Maaten, co-creator of t-SNE, on visualizing high-dimensional data by mapping it to two dimensions. It explains how the technique works and how it compares with other visualization approaches.

Hans Rosling uses the Gapminder animated-data tool to debunk myths about world development, with sportscaster-like energy. It shows trends in health, income and child survival across countries.

Steven Wittens' JSConf US 2013 talk on drawing with WebGL, using animated visuals to walk through vectors, matrices and the rendering pipeline. Despite the title, it works as a visual primer on the linear algebra behind 3D graphics.

In this TED talk, Hans Rosling uses animated statistics to debunk myths about the developing world, showing how health and income have improved across countries.

A Foresight Institute workshop video with two talks: Shawn Douglas on nanoscale instruments for visualizing small proteins, and Bret Victor on Dynamicland. Victor's part shows biomolecular design built in his Realtalk system with physical objects.

Rusty Russell and Matt Evans examine why Unix utilities like ls and cat grew from a few kilobytes to over a hundred kilobytes. They take apart common tools to see where the growth comes from.

Andrew Ng presents unsupervised feature learning and deep learning, showing how algorithms can learn representations from unlabeled data instead of hand-designed features. He gives examples in vision and audio, including visualizations of features learned by successive layers.

Chris Urmson's SXSW 2016 talk on Google's self-driving car project, covering 1.3 million self-driven miles and the gap between hype and reality. It shows sensor visualizations and playbacks of hard situations the cars met, and discusses failures such as the low-speed bus collision.

Dan Abramov's talk on the wet codebase, using visualizations to show how removing all duplication too early produces wrong abstractions that are hard to unwind.

A PyData London 2018 talk on how JPMorgan scaled its Athena Python platform over ten years to about 35 million lines of code and thousands of developers. It covers infrastructure, tooling and culture for analytics and visualization at that scale.

Adam Tornhill's GOTO Copenhagen 2019 talk on how to prioritize technical debt in large codebases. It argues for combining code complexity with change frequency (hotspots) from version control data, rather than trying to quantify debt in the abstract.

Gernot Heiser presents seL4, a microkernel with a mathematical proof connecting security properties to the binary code, and explains what its open-sourcing means for users. It covers its roles as a microkernel, separation kernel and hypervisor.