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Traceable Data Types for Self-Adjusting Computation Umut A. Acar
 

Summary: Traceable Data Types for Self-Adjusting Computation
Umut A. Acar
Max-Planck Institute
for Software Systems
umut@mpi-sws.org
Guy Blelloch Ruy Ley-Wild
Kanat Tangwongsan
Carnegie Mellon University
{blelloch,rleywild,ktangwon}@cs.cmu.edu
Duru Tšurkoglu
University of Chicago
duru@cs.uchicago.edu
Abstract
Self-adjusting computation provides an evaluation model where
computations can respond automatically to modifications to their
data by using a mechanism for propagating modifications through
the computation. Current approaches to self-adjusting computation
guarantee correctness by recording dependencies in a trace at the
granularity of individual memory operations. Tracing at the granu-
larity of memory operations, however, has some limitations: it can

  

Source: Acar, Umut - Programming Languages and Systems Group, Max-Planck Institute for Software Systems
Blelloch, Guy E. - School of Computer Science, Carnegie Mellon University

 

Collections: Computer Technologies and Information Sciences