  In this paper we analyze the computational costs of various operations and
algorithms in algebraic number fields using exact arithmetic. Let $K$ be an
algebraic number field. In the first half of the paper, we calculate the
running time and the size of the output of many operations in $K$ in terms of
the size of the input and the parameters of $K$. We include some earlier
results about these, but we go further than them, e.g. we also analyze some
$\mathbb{R}$-specific operations in $K$ like less-than comparison. In the
second half of the paper, we analyze two algorithms: the Bareiss algorithm,
which is an integer-preserving version of the Gaussian elimination, and the LLL
algorithm, which is for lattice basis reduction. In both cases, we extend the
algorithm from $\mathbb{Z}^n$ to $K^n$, and give a polynomial upper bound on
the running time when the computations in $K$ are performed exactly (as opposed
to floating-point approximations).

Symbolic Computation;Computational Complexity