func TestFindCharacteristic(t *testing.T) {
M := matrix.GenerateRandom(rand.Reader, 8)
A := matrix.GenerateRandom(rand.Reader, 8)
AInv, _ := A.Invert()
N, _ := DecomposeAffineEncoding(encoding.ComposedBytes{
encoding.ByteLinear(A),
encoding.ByteLinear(M),
encoding.ByteLinear(AInv),
})
if FindCharacteristic(M) != FindCharacteristic(N) {
t.Fatalf("FindCharacteristic was not invariant!\nM = %2.2x\nA = %2.2x\nN = %2.2x, ", M, A, N)
}
}
func BenchmarkFindCharacteristic(b *testing.B) {
M := matrix.GenerateRandom(rand.Reader, 8)
b.ResetTimer()
for i := 0; i < b.N; i++ {
FindCharacteristic(M)
}
}
func TestByteLinear(t *testing.T) {
m := ByteLinear(matrix.GenerateRandom(rand.Reader, 8))
for i := byte(0); i < 250; i++ {
for j := byte(0); j < 250; j++ {
if m.Decode(m.Encode(i)^m.Encode(j)) != i^j {
t.Fatalf("Linear encoding didn't Encode/Decode correctly.")
}
}
}
}
func BenchmarkDecomposeAffineEncoding(b *testing.B) {
aff := encoding.ByteAffine{
encoding.ByteLinear(matrix.GenerateRandom(rand.Reader, 8)),
0x60,
}
b.ResetTimer()
for i := 0; i < b.N; i++ {
DecomposeAffineEncoding(aff)
}
}
// Matrix takes a (private) seed and a (possibly public) label and produces a random non-singular 128x128 matrix.
func (rs *RandomSource) Matrix(label []byte, size int) matrix.Matrix {
key := [16]byte{}
copy(key[:], label)
cached, ok := rs.matrixCache[key]
if ok {
return cached
} else {
rs.matrixCache[key] = matrix.GenerateRandom(rs.Stream(label), size)
return rs.matrixCache[key]
}
}
