Alan Turing pioneered semantics-to-syntax analysis of algorithms. You start with a large species of algorithms, and you finish up with a syntactic artifact that characterizes the species, typically a kind of machines that compute all and only the algorithms of the species.

The task of analyzing a large species of algorithms seems daunting if not impossible. As in quicksand, one needs a rescue point, a fulcrum. In computation analysis, a fulcrum is a particular viewpoint on computation that clarifies and simplifies things to the point that analysis become possible.

We review from that point of view Turing's analysis of human-executable computation, Kolmogorov's analysis of sequential bit-level computation, Gandy's analysis of a species of machine computation, and our own analysis of sequential computation.

We also discuss limitations of semantics-to-syntax analyses.