from python import util
dataset = []
while True:
s = input()
if not s:
break
dataset.append(s)
pairs = set()
corr = []
for x in dataset:
if not x in pairs:
cx = util.reverseComplement(x)
if not cx in pairs:
pairs.add(x)
else:
pairs.remove(cx)
corr.append(x)
corr.append(cx)
else:
pairs.remove(x)
corr.append(x)
err_list = list(pairs)
for i in err_list:
for j in corr:
if util.getHammingDistance(i, j) == 1 or util.getHammingDistance(i, util.reverseComplement(j)) == 1:
print("%s->%s" % (i, j))
break
def p_distance(s, t):
return getHammingDistance(s, t) / len(s)