code: def concretize(self, symbolic, policy, maxcount=7):
          
          assert self.constraints == self.platform.constraints
          symbolic = self.migrate_expression(symbolic)
  
          vals = []
          if policy == 'MINMAX':
              vals = self._solver.minmax(self._constraints, symbolic)
          elif policy == 'MAX':
              vals = self._solver.max(self._constraints, symbolic)
          elif policy == 'MIN':
              vals = self._solver.min(self._constraints, symbolic)
          elif policy == 'SAMPLED':
              m, M = self._solver.minmax(self._constraints, symbolic)
              vals += [m, M]
              if M - m > 3:
                  if self._solver.can_be_true(self._constraints, symbolic == (m + M) // 2):
                      vals.append((m + M) // 2)
              if M - m > 100:
                  for i in (0, 1, 2, 5, 32, 64, 128, 320):
                      if self._solver.can_be_true(self._constraints, symbolic == m + i):
                          vals.append(m + i)
                      if maxcount <= len(vals):
                          break
              if M - m > 1000 and maxcount > len(vals):
                  vals += self._solver.get_all_values(self._constraints, symbolic,
                                                      maxcnt=maxcount - len(vals), silent=True)
          elif policy == 'ONE':
              vals = [self._solver.get_value(self._constraints, symbolic)]
          else:
              assert policy == 'ALL'
              vals = solver.get_all_values(self._constraints, symbolic, maxcnt=maxcount, silent=True)
  
          return tuple(set(vals))
docs: This finds a set of solutions for symbolic using policy.
              This raises TooManySolutions if more solutions than maxcount