Tootfinder

A useful tidbit that stood out to me in this article:
“Noem [by lying] is training and testing the MAGA base”
Huh − “training and testing”
There’s a dance here: the regime is training its supports in how to think about and talk about current circumstances — but also testing the waters, seeing what sticks, what they’re willing to believe. Recognizing this as a bidirectional dance seems useful. Framing it as “training” instead of “telling” seems useful. Recognizing it as “testing” seems useful.
https://thinkbigpicture.substack.com/p/ice-noem-dangerous-playbook

Stop the Government Redefining Animal Testing Sites as “National Infrastructure” #AnimalRights

Animal testing petition - Protect the Wild
Stop the Government Redefining Animal Testing Sites as “National Infrastructure” The Government is quietly pushing through a change to the law that would dramatically restrict the public’s right to protest. A new Statutory Instrument, due to be considered by MPs this week, would amend the Public Order Act 2023 to…

{testthat} is great for automatic testing. Here are some tricks for the heavy user: #rstats

Week 15 NFL anytime touchdown scorer odds, picks: Ashton Jeanty among best bets for anytime TD scorer bets

https://www.cbssports.com/nfl/news/week-15

For #TextModeTuesday, some fonts from my old demoscene days, recreated in 2022 for an example project of my opensource libraries:
Figlet style text generator using big fonts:
https://demo.thi.ng/umbrella/big-font/

Agentic Property-Based Testing: Finding Bugs Across the Python Ecosystem
Muhammad Maaz, Liam DeVoe, Zac Hatfield-Dodds, Nicholas Carlini
https://arxiv.org/abs/2510.09907 https:/…

Agentic Property-Based Testing: Finding Bugs Across the Python Ecosystem
Property-based testing (PBT) is a lightweight formal method, typically implemented as a randomized testing framework. Users specify the input domain for their test using combinators supplied by the PBT framework, and the expected properties or invariants as a unit-test function. The framework then searches for a counterexample, e.g. by generating inputs and calling the test function. In this work, we demonstrate an LLM-based agent which analyzes Python modules, infers function-specific and cros…

heise | MacBook Pro ohne Ladegerät: Diese alternativen Netzteile lohnen sich
Apple liefert nach iPhones auch erste Rechner ohne Ladegerät aus. Anlass genug, neun geeignete alternative Stromspender zu testen. Es lässt sich einiges sparen.

Agentic RAG for Software Testing with Hybrid Vector-Graph and Multi-Agent Orchestration
Mohanakrishnan Hariharan, Satish Arvapalli, Seshu Barma, Evangeline Sheela
https://arxiv.org/abs/2510.10824

Agentic RAG for Software Testing with Hybrid Vector-Graph and Multi-Agent Orchestration
We present an approach to software testing automation using Agentic Retrieval-Augmented Generation (RAG) systems for Quality Engineering (QE) artifact creation. We combine autonomous AI agents with hybrid vector-graph knowledge systems to automate test plan, case, and QE metric generation. Our approach addresses traditional software testing limitations by leveraging LLMs such as Gemini and Mistral, multi-agent orchestration, and enhanced contextualization. The system achieves remarkable accurac…

Woody Marks among Week 15's top 30 predicted anytime touchdown scorers https://www.espn.com/espn/betting/story/_/id/47279189/nfl-week-15-touchdown-odds-predictions

LLMs are All You Need? Improving Fuzz Testing for MOJO with Large Language Models
Linghan Huang, Peizhou Zhao, Huaming Chen
https://arxiv.org/abs/2510.10179 https://

LLMs are All You Need? Improving Fuzz Testing for MOJO with Large Language Models
The rapid development of large language models (LLMs) has revolutionized software testing, particularly fuzz testing, by automating the generation of diverse and effective test inputs. This advancement holds great promise for improving software reliability. Meanwhile, the introduction of MOJO, a high-performance AI programming language blending Python's usability with the efficiency of C and C++, presents new opportunities to enhance AI model scalability and programmability. However, as a new l…