SCIENCE AND NARRATIVE
How do we explain algorithms?
But narrative is everywhere.
Look at the way we explain algorithms to students -- or to our colleagues at a conference for that matter. Pick an example -- Quicksort, perhaps.
We begin with the precipitating action: a list of elements we want to sort.
We proceed to develop the action. Pick a pivot. Partition the set. Progress is made. We continue. Progress is evident -- students can see how we're approaching the goal.
But WAIT! Fate intervenes: what if we pick the wrong pivot? Performance degrades. Disaster! Failure. Can matters be salvaged? Yes! Butů.