"""E-graph backend for MBA optimization (placeholder).

This module will provide e-graph-based optimization for MBA expressions.
See docs/EGRAPH_DESIGN.md for the full design.

Future functionality:
- MBARuleset: Collection of verified MBA rules for e-graph optimization
- EGraphSimplifier: Simplify expressions using e-graph saturation
- EGraphBackend: Protocol for different e-graph implementations (egg-python, etc.)

Example usage (after implementation):
    >>> from d810.mba import Var, MBARule
    >>> from d810.mba.backends.egraph import MBARuleset, EGraphSimplifier
    >>>
    >>> # Create ruleset from verified MBA rules
    >>> ruleset = MBARuleset([XorRule1(), XorRule2()])
    >>> ruleset.verify_all()  # Z3 verifies all rules
    >>>
    >>> # Create simplifier
    >>> simplifier = EGraphSimplifier(ruleset, backend=EggBackend())
    >>>
    >>> # Simplify complex MBA expression
    >>> x, y, z = Var("x"), Var("y"), Var("z")
    >>> complex = ((x + y) - 2*(x & y) | z) - ((x + y) - 2*(x & y) & z)
    >>> simple = simplifier.simplify(complex)
    >>> print(simple)  # x ^ y ^ z
"""

# Placeholder - to be implemented as part of e-graph integration
__all__ = []

# See docs/EGRAPH_DESIGN.md for implementation details
