Why is there so much useless and unreliable software?
The adoption curve of advanced technologies that solve it all. Is it just the cognitive burden of the tooling or the concepts, are the training methods different, a dearth of already trained talent and sufficient post-graduate or post-doctoral instructors, unclear signals between demand and a supply funnel?<p>The limited availability of Formal Methods and Formal Verification training.<p>The growing demand for safety critical software for things that are heavy and that move fast and that fly over our heads and our homes.<p>In order to train, you need to present URLs: CreativeWork(s) in an outline (a tree graph), identify competencies (typically according to existing curricula) and test for comprehension, and what else is necessary to boost retention for and of identified competencies?<p>There are many online courses, but so few on Computer Science Education. You can  teach with autograded Jupyter notebooks and your own edX instance all hosted in OCI containers in your own Kubernetes cloud, for example. Containers and Ansible Playbooks help minimize cost and variance in that part of the learning stack.<p>We should all learn Coq and TLA+ and Lean, especially. What resources and traversal do you recommend for these possibly indeed core competencies? For which domains are no-code tools safe?<p>If we were to instead have our LLM (,ChatGPT,Codex,) filter expression trees in order to autocomplete from <i>only</i> Formally Verified code with associated Automated Tests, and e.g. Lean Mathlib, how would our output differ from that of an LLM training on code that may or may not have any tests?<p>Could that also implement POSIX and which other interfaces, please?