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A = read($X);
B = smote(X = A, s=$S, k=$K);

# test if all point fall in same cluster (closed to each other)
# read some new data T != A 
T = read($T);
# bind all instanced of minority class
A_B = rbind(A, B)
n = nrow(A_B)
# group data into k=2 clusters
[C, Y] = kmeans(rbind(A_B, T),  2, 10, 100, 0.000001, FALSE, 50)
# check if the instances of A and B fall in same cluster
check = matrix(as.scalar(Y[1,1]), n, 1)
testSum = sum(check - Y[1:n,])
# hack for avoiding null pointer exception while reading a single zero in HashMap
testSum = ifelse(testSum == 0, 1, testSum)
testSum = as.matrix(testSum)
write(testSum, $Z);