A QR code that sends you to a different destination – lenticular and adversarial
mstdn.social
Thank HN: My bootstrapped startup got acquired today
New Electrical Code Could Doom Most Common EV Charging
motortrend.com
UI is hell: four-function calculators
lcamtuf.substack.com
Show HN: I made an open-source laptop from scratch
byran.ee
Llama.vim – Local LLM-assisted text completion
github.com
Operator research preview
openai.com
Supercharge vector search with ColBERT rerank in PostgreSQL
blog.vectorchord.ai
Building a Medieval Castle from Scratch
guedelon.fr
Susctl CVE-2024-54507: A particularly 'sus' sysctl in the XNU kernel
jprx.io
LoongArch64 Subjective Higlights
0x80.pl
Surface-Stable Fractal Dithering
github.com
Disabling Zen 5's Op Cache and Exploring Its Clustered Decoder
chipsandcheese.com
Psychedelic Graphics 0: Introduction
benpence.com
Hacking Subaru: Tracking and controlling cars via the admin panel
samcurry.net
Show HN: Open-source AI video editor
github.com
Show HN: I built an active community of trans people online
t4t.social
Find Your Footing After Installing Arch Linux
ejmastnak.com
Working with Files Is Hard (2019)
danluu.com
Building a full-text search engine in 150 lines of Python code (2021)
bart.degoe.de
Abstract:
"We present the design of CompFuzzCI, a framework for incorporating compiler fuzzing into the continuous integration (CI) workflow of the compiler for Dafny, an open-source programming language that is increasingly used in and contributed to by industry. CompFuzzCI explores the idea of running a brief fuzzing campaign as part of the CI workflow of each pull request to a compiler project. Making this effective involved devising solutions for various challenges, including how to deduplicate bugs, how to bisect the project’s revision history to find the commit responsible for a regression (challenging when project interfaces change over time), and how to ensure that fuzz testing complements existing regression testing efforts. We explain how we have engaged with the Dafny development team at Amazon to approach these and other problems in the design of CompFuzzCI, and the lessons learned in the process. As a by-product of our work with CompFuzzCI, we found and reported three previously-unknown bugs in the Dafny compiler. We also present a controlled experiment simulating the use of CompFuzzCI over time on a range of Dafny commits, to assess its ability to find historic bugs. CompFuzzCI prioritises support for the Dafny compiler and the fuzz-d fuzzer but has a generalisable design: with modest modification to its internal interfaces, it could be adapted to work with other fuzzers, and the lessons learned from our experience will be relevant to teams considering including fuzzing in the CI of other industrial software projects."
https://github.com/CompFuzzCI