Many researchers have proposed programming languages that support incremental
computation (IC), which allows programs to be efficiently re-executed after a small change to …

We present techniques for incremental computing by introducing adaptive functional
programming. As an adaptive program executes, the underlying system represents the data …

Large Scale and Big Data: Processing and Management provides readers with a central
source of reference on the data management techniques currently available for large-scale …

Self-adjusting computation enables writing programs that can automatically and efficiently
respond to changes to their data (eg, inputs). The idea behind the approach is to store all …

Recent work on adaptive functional programming (AFP) developed techniques for writing
programs that can respond to modifications to their data by performing change propagation …

Over the past thirty years, there has been significant progress in developing general-
purpose, language-based approaches to incremental computation, which aims to efficiently …

Parallel or incremental versions of an algorithm can significantly outperform their
counterparts, but are often difficult to develop. Programming models that provide appropriate …

With recent advances, programs can be compiled to efficiently respond to incremental input
changes. However, there is no language-level support for reasoning about the time …

Online streaming algorithms, tailored for continuous data processing, offer substantial
benefits but are often more intricate to design than their offline counterparts. This paper …

Dependence graphs and memoization can be used to efficiently update the output of a
program as the input changes dynamically. Recent work has studied techniques for …