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Summary: A Cost Semantics for Self-Adjusting Computation
Ruy Ley-Wild
Carnegie Mellon University
rleywild@cs.cmu.edu
Umut A. Acar Matthew Fluet
Toyota Technological Institute at Chicago
{acar,fluet}@tti-c.org
Abstract
Self-adjusting computation is an evaluation model in which pro-
grams can respond efficiently to small changes to their input data by
using a change-propagation mechanism that updates computation
by re-building only the parts affected by changes. Previous work
has proposed language techniques for self-adjusting computation
and showed the approach to be effective in a number of application
areas. However, due to the complex semantics of change propaga-
tion and the indirect nature of previously proposed language tech-
niques, it remains difficult to reason about the efficiency of self-
adjusting programs and change propagation.
In this paper, we propose a cost semantics for self-adjusting
computation that enables reasoning about its effectiveness. As our
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