Suppose a user propagator encodes axioms using quantifiers and uses E-matching for instantiation. If it wants to implement a custom priority scheme or drop some instances based on internal checks it can register a callback with quantifier instantiation
* 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.
simplify assumptions and only replay assumptions after constraints are simplified. This allows simplifying assumptions with the current set of constraints independently of whether there is another check-sat.
Add the ability to customize incremental pre-processing simplification for the SMTLIB2 front-end. The main new capability is to use pre-processing tactics in incremental mode that were previously not available. The main new capabilities are
- solve-eqs
- reduce-args
- elim-unconstrained
There are several more. Documentation and exposed simplifiers are populated incrementally. The current set of supported simplifiers can be inspected by using z3 with the --simplifiers flag or referring to https://microsoft.github.io/z3guide/docs/strategies/simplifiers
Some pending features are:
- add the ability to update parameters to simplifiers similar to how tactics can be controlled using parameters.
- expose simplification solvers over the binary API.
move sat_smt_preprocess to solver
fix bugs in model_reconstruction_trail for dependency replay
This is a preparatory step for exposing pre-processing as tactics.
