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+# This code supports verifying group implementations which have branches
+# or conditional statements (like cmovs), by allowing each execution path
+# to independently set assumptions on input or intermediary variables.
+#
+# The general approach is:
+# * A constraint is a tuple of two sets of of symbolic expressions:
+#   the first of which are required to evaluate to zero, the second of which
+#   are required to evaluate to nonzero.
+#   - A constraint is said to be conflicting if any of its nonzero expressions
+#     is in the ideal with basis the zero expressions (in other words: when the
+#     zero expressions imply that one of the nonzero expressions are zero).
+# * There is a list of laws that describe the intended behaviour, including
+#   laws for addition and doubling. Each law is called with the symbolic point
+#   coordinates as arguments, and returns:
+#   - A constraint describing the assumptions under which it is applicable,
+#     called "assumeLaw"
+#   - A constraint describing the requirements of the law, called "require"
+# * Implementations are transliterated into functions that operate as well on
+#   algebraic input points, and are called once per combination of branches
+#   exectured. Each execution returns:
+#   - A constraint describing the assumptions this implementation requires
+#     (such as Z1=1), called "assumeFormula"
+#   - A constraint describing the assumptions this specific branch requires,
+#     but which is by construction guaranteed to cover the entire space by
+#     merging the results from all branches, called "assumeBranch"
+#   - The result of the computation
+# * All combinations of laws with implementation branches are tried, and:
+#   - If the combination of assumeLaw, assumeFormula, and assumeBranch results
+#     in a conflict, it means this law does not apply to this branch, and it is
+#     skipped.
+#   - For others, we try to prove the require constraints hold, assuming the
+#     information in assumeLaw + assumeFormula + assumeBranch, and if this does
+#     not succeed, we fail.
+#     + To prove an expression is zero, we check whether it belongs to the
+#       ideal with the assumed zero expressions as basis. This test is exact.
+#     + To prove an expression is nonzero, we check whether each of its
+#       factors is contained in the set of nonzero assumptions' factors.
+#       This test is not exact, so various combinations of original and
+#       reduced expressions' factors are tried.
+#   - If we succeed, we print out the assumptions from assumeFormula that
+#     weren't implied by assumeLaw already. Those from assumeBranch are skipped,
+#     as we assume that all constraints in it are complementary with each other.
+#
+# Based on the sage verification scripts used in the Explicit-Formulas Database
+# by Tanja Lange and others, see http://hyperelliptic.org/EFD
+
+class fastfrac:
+  """Fractions over rings."""
+
+  def __init__(self,R,top,bot=1):
+    """Construct a fractional, given a ring, a numerator, and denominator."""
+    self.R = R
+    if parent(top) == ZZ or parent(top) == R:
+      self.top = R(top)
+      self.bot = R(bot)
+    elif top.__class__ == fastfrac:
+      self.top = top.top
+      self.bot = top.bot * bot
+    else:
+      self.top = R(numerator(top))
+      self.bot = R(denominator(top)) * bot
+
+  def iszero(self,I):
+    """Return whether this fraction is zero given an ideal."""
+    return self.top in I and self.bot not in I
+
+  def reduce(self,assumeZero):
+    zero = self.R.ideal(map(numerator, assumeZero))
+    return fastfrac(self.R, zero.reduce(self.top)) / fastfrac(self.R, zero.reduce(self.bot))
+
+  def __add__(self,other):
+    """Add two fractions."""
+    if parent(other) == ZZ:
+      return fastfrac(self.R,self.top + self.bot * other,self.bot)
+    if other.__class__ == fastfrac:
+      return fastfrac(self.R,self.top * other.bot + self.bot * other.top,self.bot * other.bot)
+    return NotImplemented
+
+  def __sub__(self,other):
+    """Subtract two fractions."""
+    if parent(other) == ZZ:
+      return fastfrac(self.R,self.top - self.bot * other,self.bot)
+    if other.__class__ == fastfrac:
+      return fastfrac(self.R,self.top * other.bot - self.bot * other.top,self.bot * other.bot)
+    return NotImplemented
+
+  def __neg__(self):
+    """Return the negation of a fraction."""
+    return fastfrac(self.R,-self.top,self.bot)
+
+  def __mul__(self,other):
+    """Multiply two fractions."""
+    if parent(other) == ZZ:
+      return fastfrac(self.R,self.top * other,self.bot)
+    if other.__class__ == fastfrac:
+      return fastfrac(self.R,self.top * other.top,self.bot * other.bot)
+    return NotImplemented
+
+  def __rmul__(self,other):
+    """Multiply something else with a fraction."""
+    return self.__mul__(other)
+
+  def __div__(self,other):
+    """Divide two fractions."""
+    if parent(other) == ZZ:
+      return fastfrac(self.R,self.top,self.bot * other)
+    if other.__class__ == fastfrac:
+      return fastfrac(self.R,self.top * other.bot,self.bot * other.top)
+    return NotImplemented
+
+  def __pow__(self,other):
+    """Compute a power of a fraction."""
+    if parent(other) == ZZ:
+      if other < 0:
+        # Negative powers require flipping top and bottom
+        return fastfrac(self.R,self.bot ^ (-other),self.top ^ (-other))
+      else:
+        return fastfrac(self.R,self.top ^ other,self.bot ^ other)
+    return NotImplemented
+
+  def __str__(self):
+    return "fastfrac((" + str(self.top) + ") / (" + str(self.bot) + "))"
+  def __repr__(self):
+    return "%s" % self
+
+  def numerator(self):
+    return self.top
+
+class constraints:
+  """A set of constraints, consisting of zero and nonzero expressions.
+
+  Constraints can either be used to express knowledge or a requirement.
+
+  Both the fields zero and nonzero are maps from expressions to description
+  strings. The expressions that are the keys in zero are required to be zero,
+  and the expressions that are the keys in nonzero are required to be nonzero.
+
+  Note that (a != 0) and (b != 0) is the same as (a*b != 0), so all keys in
+  nonzero could be multiplied into a single key. This is often much less
+  efficient to work with though, so we keep them separate inside the
+  constraints. This allows higher-level code to do fast checks on the individual
+  nonzero elements, or combine them if needed for stronger checks.
+
+  We can't multiply the different zero elements, as it would suffice for one of
+  the factors to be zero, instead of all of them. Instead, the zero elements are
+  typically combined into an ideal first.
+  """
+
+  def __init__(self, **kwargs):
+    if 'zero' in kwargs:
+      self.zero = dict(kwargs['zero'])
+    else:
+      self.zero = dict()
+    if 'nonzero' in kwargs:
+      self.nonzero = dict(kwargs['nonzero'])
+    else:
+      self.nonzero = dict()
+
+  def negate(self):
+    return constraints(zero=self.nonzero, nonzero=self.zero)
+
+  def __add__(self, other):
+    zero = self.zero.copy()
+    zero.update(other.zero)
+    nonzero = self.nonzero.copy()
+    nonzero.update(other.nonzero)
+    return constraints(zero=zero, nonzero=nonzero)
+
+  def __str__(self):
+    return "constraints(zero=%s,nonzero=%s)" % (self.zero, self.nonzero)
+
+  def __repr__(self):
+    return "%s" % self
+
+
+def conflicts(R, con):
+  """Check whether any of the passed non-zero assumptions is implied by the zero assumptions"""
+  zero = R.ideal(map(numerator, con.zero))
+  if 1 in zero:
+    return True
+  # First a cheap check whether any of the individual nonzero terms conflict on
+  # their own.
+  for nonzero in con.nonzero:
+    if nonzero.iszero(zero):
+      return True
+  # It can be the case that entries in the nonzero set do not individually
+  # conflict with the zero set, but their combination does. For example, knowing
+  # that either x or y is zero is equivalent to having x*y in the zero set.
+  # Having x or y individually in the nonzero set is not a conflict, but both
+  # simultaneously is, so that is the right thing to check for.
+  if reduce(lambda a,b: a * b, con.nonzero, fastfrac(R, 1)).iszero(zero):
+    return True
+  return False
+
+
+def get_nonzero_set(R, assume):
+  """Calculate a simple set of nonzero expressions"""
+  zero = R.ideal(map(numerator, assume.zero))
+  nonzero = set()
+  for nz in map(numerator, assume.nonzero):
+    for (f,n) in nz.factor():
+      nonzero.add(f)
+    rnz = zero.reduce(nz)
+    for (f,n) in rnz.factor():
+      nonzero.add(f)
+  return nonzero
+
+
+def prove_nonzero(R, exprs, assume):
+  """Check whether an expression is provably nonzero, given assumptions"""
+  zero = R.ideal(map(numerator, assume.zero))
+  nonzero = get_nonzero_set(R, assume)
+  expl = set()
+  ok = True
+  for expr in exprs:
+    if numerator(expr) in zero:
+      return (False, [exprs[expr]])
+  allexprs = reduce(lambda a,b: numerator(a)*numerator(b), exprs, 1)
+  for (f, n) in allexprs.factor():
+    if f not in nonzero:
+      ok = False
+  if ok:
+    return (True, None)
+  ok = True
+  for (f, n) in zero.reduce(numerator(allexprs)).factor():
+    if f not in nonzero:
+      ok = False
+  if ok:
+    return (True, None)
+  ok = True
+  for expr in exprs:
+    for (f,n) in numerator(expr).factor():
+      if f not in nonzero:
+        ok = False
+  if ok:
+    return (True, None)
+  ok = True
+  for expr in exprs:
+    for (f,n) in zero.reduce(numerator(expr)).factor():
+      if f not in nonzero:
+        expl.add(exprs[expr])
+  if expl:
+    return (False, list(expl))
+  else:
+    return (True, None)
+
+
+def prove_zero(R, exprs, assume):
+  """Check whether all of the passed expressions are provably zero, given assumptions"""
+  r, e = prove_nonzero(R, dict(map(lambda x: (fastfrac(R, x.bot, 1), exprs[x]), exprs)), assume)
+  if not r:
+    return (False, map(lambda x: "Possibly zero denominator: %s" % x, e))
+  zero = R.ideal(map(numerator, assume.zero))
+  nonzero = prod(x for x in assume.nonzero)
+  expl = []
+  for expr in exprs:
+    if not expr.iszero(zero):
+      expl.append(exprs[expr])
+  if not expl:
+    return (True, None)
+  return (False, expl)
+
+
+def describe_extra(R, assume, assumeExtra):
+  """Describe what assumptions are added, given existing assumptions"""
+  zerox = assume.zero.copy()
+  zerox.update(assumeExtra.zero)
+  zero = R.ideal(map(numerator, assume.zero))
+  zeroextra = R.ideal(map(numerator, zerox))
+  nonzero = get_nonzero_set(R, assume)
+  ret = set()
+  # Iterate over the extra zero expressions
+  for base in assumeExtra.zero:
+    if base not in zero:
+      add = []
+      for (f, n) in numerator(base).factor():
+        if f not in nonzero:
+          add += ["%s" % f]
+      if add:
+        ret.add((" * ".join(add)) + " = 0 [%s]" % assumeExtra.zero[base])
+  # Iterate over the extra nonzero expressions
+  for nz in assumeExtra.nonzero:
+    nzr = zeroextra.reduce(numerator(nz))
+    if nzr not in zeroextra:
+      for (f,n) in nzr.factor():
+        if zeroextra.reduce(f) not in nonzero:
+          ret.add("%s != 0" % zeroextra.reduce(f))
+  return ", ".join(x for x in ret)
+
+
+def check_symbolic(R, assumeLaw, assumeAssert, assumeBranch, require):
+  """Check a set of zero and nonzero requirements, given a set of zero and nonzero assumptions"""
+  assume = assumeLaw + assumeAssert + assumeBranch
+
+  if conflicts(R, assume):
+    # This formula does not apply
+    return None
+
+  describe = describe_extra(R, assumeLaw + assumeBranch, assumeAssert)
+
+  ok, msg = prove_zero(R, require.zero, assume)
+  if not ok:
+    return "FAIL, %s fails (assuming %s)" % (str(msg), describe)
+
+  res, expl = prove_nonzero(R, require.nonzero, assume)
+  if not res:
+    return "FAIL, %s fails (assuming %s)" % (str(expl), describe)
+
+  if describe != "":
+    return "OK (assuming %s)" % describe
+  else:
+    return "OK"
+
+
+def concrete_verify(c):
+  for k in c.zero:
+    if k != 0:
+      return (False, c.zero[k])
+  for k in c.nonzero:
+    if k == 0:
+      return (False, c.nonzero[k])
+  return (True, None)