Summary:
It improves the precision of widening operations of interval:
upper_bound_widen (min(n, s), s) = s
lower_bound_widen (max(n, s), s) = s
Reviewed By: mbouaziz
Differential Revision: D8038941
fbshipit-source-id: 61b10cb
Summary:
Before we were computing the size of an abstract state (`range`) using the `NonNegativeBound` domain but it wasn't able to express product of symbolic values.
This diff introduces a domain for that.
The range of an interval is still computed in `NonNegativeBound` but then the product is done in `TopLiftedPolynomial` so all costs end up being of that type.
The //symbols// of a polynomial are `NonNegativeBound` (so the polynomial only represent non-negative values, perfect for a cost), which handles substitution correctly, i.e. it gives zero instead of negative values.
Reviewed By: ddino
Differential Revision: D7397229
fbshipit-source-id: 6868bb7
Summary: We were wrongly using the underapproximation of `min` rather than the overapproximation
Reviewed By: ddino
Differential Revision: D7844267
fbshipit-source-id: c9d9247
Summary:
We want instr-granular invariant maps so let's use the OneInstrPerNode CFG in the AI analyzers.
This requires specializing the TransferFunctions.
Keep using the normal CFG where we only need node-granular informations.
Depends on D7587241
Depends on D7608526
Reviewed By: sblackshear
Differential Revision: D7618320
fbshipit-source-id: 73918f0
Sungkeun Cho
Ezgi Çiçek
Mehdi Bouaziz
Dino Distefano