* Introduce X-macro-based trace tag definition
- Created trace_tags.def to centralize TRACE tag definitions
- Each tag includes a symbolic name and description
- Set up enum class TraceTag for type-safe usage in TRACE macros
* Add script to generate Markdown documentation from trace_tags.def
- Python script parses trace_tags.def and outputs trace_tags.md
* Refactor TRACE_NEW to prepend TraceTag and pass enum to is_trace_enabled
* trace: improve trace tag handling system with hierarchical tagging
- Introduce hierarchical tag-class structure: enabling a tag class activates all child tags
- Unify TRACE, STRACE, SCTRACE, and CTRACE under enum TraceTag
- Implement initial version of trace_tag.def using X(tag, tag_class, description)
(class names and descriptions to be refined in a future update)
* trace: replace all string-based TRACE tags with enum TraceTag
- Migrated all TRACE, STRACE, SCTRACE, and CTRACE macros to use enum TraceTag values instead of raw string literals
* trace : add cstring header
* trace : Add Markdown documentation generation from trace_tags.def via mk_api_doc.py
* trace : rename macro parameter 'class' to 'tag_class' and remove Unicode comment in trace_tags.h.
* trace : Add TODO comment for future implementation of tag_class activation
* trace : Disable code related to tag_class until implementation is ready (#7663).
Add API solve_for(vars).
It takes a list of variables and returns a triangular solved form for the variables.
Currently for arithmetic. The solved form is a list with elements of the form (var, term, guard).
Variables solved in the tail of the list do not occur before in the list.
For example it can return a solution [(x, z, True), (y, x + z, True)] because first x was solved to be z,
then y was solved to be x + z which is the same as 2z.
Add congruent_explain that retuns an explanation for congruent terms.
Terms congruent in the final state after calling SimpleSolver().check() can be queried for
an explanation, i.e., a list of literals that collectively entail the equality under congruence closure.
The literals are asserted in the final state of search.
Adjust smt_context cancellation for the smt.qi.max_instantiations parameter.
It gets checked when qi-queue elements are consumed.
Prior it was checked on insertion time, which didn't allow for processing as many
instantations as there were in the queue. Moreover, it would not cancel the solver.
So it would keep adding instantations to the queue when it was full / depleted the
configuration limit.
this will allow copying the solver state within a scope.
The new solver state has its state at level 0. It is not possible to pop scopes from the new solver (you can still pop scopes from the original solver). The reason for this semantics is the relative difficulty of implementing (getting it right) of a state copy that preserves scopes.
This update includes an experimental feature to access a congruence closure data-structure after search.
It comes with several caveats as pre-processing is free to eliminate terms. It is therefore necessary to use a solver that does not eliminate the terms you want to track for congruence of. This is partially addressed by using SimpleSolver or incremental mode solving.
```python
from z3 import *
s = SimpleSolver()
x, y, z = Ints('x y z')
s.add(x == y)
s.add(y == z)
s.check()
print(s.root(x), s.root(y), s.root(z))
print(s.next(x), s.next(y), s.next(z))
```
