Incremental computation via function caching
POPL '89 Proceedings of the 16th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Skip lists: a probabilistic alternative to balanced trees
Communications of the ACM
Randomized multidimensional search trees: lazy balancing and dynamic shuffling (extended abstract)
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
Systematic derivation of incremental programs
Science of Computer Programming
Caching function calls using precise dependencies
PLDI '00 Proceedings of the ACM SIGPLAN 2000 conference on Programming language design and implementation
ICFP '00 Proceedings of the fifth ACM SIGPLAN international conference on Functional programming
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Design of Dynamic Data Structures
Design of Dynamic Data Structures
Incremental evaluation for attribute grammars with application to syntax-directed editors
POPL '81 Proceedings of the 8th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Monads for incremental computing
Proceedings of the seventh ACM SIGPLAN international conference on Functional programming
POPL '03 Proceedings of the 30th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Dynamizing static algorithms, with applications to dynamic trees and history independence
SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
Self-adjusting computation
Computational Geometry: Algorithms and Applications
Computational Geometry: Algorithms and Applications
New classes and applications of hash functions
SFCS '79 Proceedings of the 20th Annual Symposium on Foundations of Computer Science
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
Imperative self-adjusting computation
Proceedings of the 35th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Compiling self-adjusting programs with continuations
Proceedings of the 13th ACM SIGPLAN international conference on Functional programming
An experimental analysis of self-adjusting computation
ACM Transactions on Programming Languages and Systems (TOPLAS)
Two for the price of one: a model for parallel and incremental computation
Proceedings of the 2011 ACM international conference on Object oriented programming systems languages and applications
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We present a Standard ML library for writing programs that automatically adjust to changes to their data. The library combines modifiable references and memoization to achieve efficient updates. We describe an implementation of the library and apply it to the problem of maintaining the convex hull of a dynamically changing set of points. Our experiments show that the overhead of the library is small, and that self-adjusting programs can adjust to small changes three-orders of magnitude faster than recomputing from scratch. The implementation relies on invariants that could be enforced by a modal type system. We show, using an existing language, abstract interfaces for modifiable references and for memoization that ensure the same safety properties without the use of modal types. The interface for memoization, however, does not scale well, suggesting a language-based approach to be preferable after all.