An introduction to the theory of lists
Proceedings of the NATO Advanced Study Institute on Logic of programming and calculi of discrete design
Formal derivation of efficient parallel programs by construction of list homomorphisms
ACM Transactions on Programming Languages and Systems (TOPLAS)
Parallelization in calculational forms
POPL '98 Proceedings of the 25th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
QuickCheck: a lightweight tool for random testing of Haskell programs
ICFP '00 Proceedings of the fifth ACM SIGPLAN international conference on Functional programming
Introduction to Functional Programming
Introduction to Functional Programming
Systematic Extraction and Implementation of Divide-and-Conquer Parallelism
PLILP '96 Proceedings of the 8th International Symposium on Programming Languages: Implementations, Logics, and Programs
Patterns and skeletons for parallel and distributed computing
Patterns and skeletons for parallel and distributed computing
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Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programming
A library of constructive skeletons for sequential style of parallel programming
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
Automatic inversion generates divide-and-conquer parallel programs
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Google's MapReduce programming model – Revisited
Science of Computer Programming
The third homomorphism theorem on trees: downward & upward lead to divide-and-conquer
Proceedings of the 36th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Calculational parallel programming: parallel programming with homomorphism and mapreduce
Proceedings of the fourth international workshop on High-level parallel programming and applications
ESOP'12 Proceedings of the 21st European conference on Programming Languages and Systems
Proceedings of the 2013 International Workshop on Programming Models and Applications for Multicores and Manycores
A short cut to parallelization theorems
Proceedings of the 18th ACM SIGPLAN international conference on Functional programming
Proceedings of the 2nd ACM SIGPLAN workshop on Functional high-performance computing
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MapReduce is a useful and popular programming model for data-intensive distributed parallel computing. But it is still a challenge to develop parallel programs with MapReduce systematically, since it is usually not easy to derive a proper divide-and-conquer algorithm that matches MapReduce. In this paper, we propose a homomorphism-based framework named Screwdriver for systematic parallel programming with MapReduce, making use of the program calculation theory of list homomorphisms. Screwdriver is implemented as a Java library on top of Hadoop. For any problem which can be resolved by two sequential functions that satisfy the requirements of the third homomorphism theorem, Screwdriver can automatically derive a parallel algorithm as a list homomorphism and transform the initial sequential programs to an efficient MapReduce program. Users need neither to care about parallelism nor to have deep knowledge of MapReduce. In addition to the simplicity of the programming model of our framework, such a calculational approach enables us to resolve many problems that it would be nontrivial to resolve directly with MapReduce.