Academic literature on the topic 'Number theory – Explicit machine computation and programs (not the theory of computation or programming)'

Program generation has the prospect of being an integral part of a wide range of software development processes. Recent studies investigate different aspects of program generation systems, including their semantics, their applications, and their implementation. Existing theories and systems address both high-level (source) language and low-level (machine) language generation. A number of programming languages now support program generation and manipulation, with different goals, implementation techniques, and targeted at different applications. In this context, a PLI workshop dedicated to this theme (SAIG'00) was held in Montreal in September 2000. Following on from this workshop, a special issue of the Journal of Functional Programming will be devoted to the same theme.Full-length, archival-quality submissions are solicited on topics including both theoretical and practical models and tools for building program generation systems, Examples include:[bull ] Semantics, type systems, and implementations for multi-stage languages.[bull ] Run-time specialization systems, e.g. compilers, operating systems.[bull ] High-level program generation (applications, foundations, environments).[bull ] Symbolic computation, linking and explicit substitution, in-lining and macros.Reports on applications of these techniques to real-world problems are especially encouraged, as are submissions that relate ideas and concepts from several of these topics, or bridge the gap between theory and practice.Contributors to SAIG'00 are encouraged to submit, but submission is open to everyone. Papers will be reviewed as regular JFP submissions, and acceptance in the special issue will be based on relevance to the theme. The special issue also welcomes high-quality survey and position papers that would benefit a wide audience. Accepted papers exceeding the space restrictions will be published as regular JFP papers.Submissions should be sent to the guest editor (address below), with a copy to Nasreen Ahmad (nasreen@dcs.gla.ac.uk). Submitted articles should be sent in postscript format, preferably gzipped and uuencoded. In addition, please send, as plain text, title, abstract, and contact information. The submission deadline is 1st February 2001. For other submission details, please consult an issue of the Journal of Functional Programming or see the Journal's web page at http://www.dcs.gla.ac.uk/jfp/.

Imagine your local creamery administers a survey asking their patrons to choose their five favorite ice cream flavors. Any data collected by this survey would be an example of partially ranked data, as the set of all possible flavors is only ranked into subsets of the chosen flavors and the non-chosen flavors. If the creamery asks you to help analyze this data, what approaches could you take? One approach is to use the natural symmetries of the underlying data space to decompose any data set into smaller parts that can be more easily understood. In this work, I describe how to use permutation representations of the symmetric group to create and study efficient algorithms that yield such decompositions.