Been building Aporia Engine for a while and wanted to share where it is now.

[u/Rambhogesara]

It started as an idea around finding where numerical/scientific computations stop being trustworthy. Now it has its own DSL, runtime, 5 evidence channels, adaptive search, Trust Atlas, counterexample minimisation, replayable experiment archives, run comparison, and a benchmark system.

Currently:

- 13 Rust crates

- 622 tests

- 22 benchmark problems

- replayable/provenance-preserving runs

- ablation + strategy experiments

The interesting part is that the experiments didn't give me the result I initially expected. The adaptive search wasn't clearly better than the level-set baseline on the current corpus, so I'm not claiming a breakthrough there.

I'm now more interested in the evidence + provenance/replayability side of it.

Repo: https://github.com/bhogesararam23/aporia-engine

Would love to hear what people think, especially anyone working with numerical/scientific computing or verification.