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In computer science, pseudocode is a description of the steps in an algorithm using a mix of conventions of programming languages with informal, usually self-explanatory, notation of actions and conditions. Although pseudocode shares features with regular programming languages, it is intended for human reading rather than machine control. Pseudocode typically omits details that are essential for machine implementation of the algorithm, meaning that pseudocode can only be verified by hand. The programming language is augmented with natural language description details, where convenient, or with compact mathematical notation. The purpose of using pseudocode is that it is easier for people to understand than conventional programming language code, and that it is an efficient and environment-independent description of the key principles of an algorithm. It is commonly used in textbooks and scientific publications to document algorithms and in planning of software and other algorithms.
Reconfigurable computing is a computer architecture combining some of the flexibility of software with the high performance of hardware by processing with flexible hardware platforms like field-programmable gate arrays (FPGAs). The principal difference when compared to using ordinary microprocessors is the ability to add custom computational blocks using FPGAs. On the other hand, the main difference from custom hardware, i.e. application-specific integrated circuits (ASICs) is the possibility to adapt the hardware during runtime by "loading" a new circuit on the reconfigurable fabric, thus providing new computational blocks without the need to manufacture and add new chips to the existing system.
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A term graph is a representation of an expression in a formal language as a generalized graph whose vertices are terms. Term graphs are a more powerful form of representation than expression trees because they can represent not only common subexpressions but also cyclic/recursive subexpressions.
In rewriting, a reduction strategy or rewriting strategy is a relation specifying a rewrite for each object or term, compatible with a given reduction relation. Some authors use the term to refer to an evaluation strategy.
Inductive programming (IP) is a special area of automatic programming, covering research from artificial intelligence and programming, which addresses learning of typically declarative and often recursive programs from incomplete specifications, such as input/output examples or constraints.
John Darlington is a British academic, researcher and author. He is an Emeritus Professor at Imperial College London. He was Director of the London e-Science Centre and was head of the Functional Programming and Social Computing Sections at Imperial.
References
- ↑ Clarke, T. J.W.; Gladstone, P. J.S.; MacLean, C. D.; Norman, A. C. (25 August 1980). "SKIM - the S, K, I reduction machine". Proceedings of the 1980 ACM conference on LISP and functional programming - LFP '80. LFP '80. New York, NY, USA: Association for Computing Machinery. pp. 128–135. doi:10.1145/800087.802798. ISBN 978-1-4503-7396-8. S2CID 10189254.
- ↑ "Reduction Machines". 31 July 2002. Archived from the original on 31 July 2002. Retrieved 1 July 2023.
- ↑ Jones, Simon L. Peyton; Clack, Chris; Salkild, Jon; Hardie, Mark (1987). "GRIP — a high-performance architecture for parallel graph reduction". In Kahn, Gilles (ed.). Functional Programming Languages and Computer Architecture. Lecture Notes in Computer Science. Vol. 274. Berlin, Heidelberg: Springer. pp. 98–112. doi: 10.1007/3-540-18317-5_7 . ISBN 978-3-540-47879-9.
- ↑ Naylor, Matthew; Runciman, Colin (2012). "The Reduceron reconfigured and re-evaluated". Journal of Functional Programming. 22 (4–5): 574–613. doi: 10.1017/S0956796812000214 . ISSN 1469-7653. S2CID 1310090.
- ↑ Naylor, Matthew; Runciman, Colin (2008). "The Reduceron: Widening the von Neumann Bottleneck for Graph Reduction Using an FPGA". In Chitil, Olaf; Horváth, Zoltán; Zsók, Viktória (eds.). Implementation and Application of Functional Languages. Lecture Notes in Computer Science. Vol. 5083. Berlin, Heidelberg: Springer. pp. 129–146. doi:10.1007/978-3-540-85373-2_8. ISBN 978-3-540-85373-2.
