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$\mathbf{L}$ consists of decision problems solvable by a deterministic logarithmic space computation.

$\mathbf{NL}$ consists of decision problems solvable by a nondeterministic logarithmic space computation.

A decision problem $B$ is NL-complete when $B\in \mathbf{NL}$ and every language $A\in \mathbf{NL}$ has a deterministic logarithmic space many-one reduction to $B$.

The directed graph reachability problem is the standard example. It lies in NL because a machine stores the current vertex and a counter, nondeterministically guesses at most $|V|-1$ successive edges, and accepts upon reaching $t$; this uses $O(\log |V|)$ space. For hardness, given an NL machine $M$ and input $x$, construct its configuration graph. Its configurations have logarithmic length, adjacency can be computed in logarithmic space, andAdding one target joined from every accepting configuration gives the required logarithmic-space reduction.