41. Computer Science (CSC) - Course Catalogue - Cornell College Alternative programming paradigms, including functional languages. Programming examples from selected languages. Prerequisites CSC 213 and 218. http://www.cornellcollege.edu/catalogue/current/courses-of-instruction/csc.shtml

Apply Calendar Directory Contact Us ... Courses of Instruction Computer Science (CSC) Tony deLaubenfels (chair), Leon Tabak The technology of computing has developed with unprecedented speed and offers the prospect of continued rapid advance. Few technologies have so quickly become so pervasive. Few have so profoundly changed science, business and industry, and government. Some understanding of the potential and limitations of computing is essential to anyone who wishes to understand modern society. Design, experiment, and analysis: these skills make the computer scientist part engineer, part scientist, and part mathematician. The student of computer science learns how to effectively communicate with teammates and clients to define problems and their solutions. Students learn how to divide a complex problem into pieces of manageable size, to organize and relate the pieces of information that describe the problem, and to order the steps of the solution. The study of computer science serves to increase a student's awareness of the necessity of constructing a hierarchy of abstractions as a means of building and understanding complex machines, the designer's need to give balanced consideration to competing goals, e.g., minimizing cost while maximizing computational speed, and the relationship between software and hardware. Major : A minimum of ten course credits, including nine in Computer Science; also MAT

42. Selected Papers Comparing Parallel Functional Languages Programming and Performance, in Higherorder and Symbolic Computation, 2003 K. Hammond, J. Berthold and R. Loogen http://www.mathematik.uni-marburg.de/~loogen/research.html

Research Areas of Rita Loogen Parallel Functional Programming Integration of Functional and Logic Programming Languages Parallel Implementation of Functional Languages Selected Papers Parallel Functional Programming The Eden Project Jost Berthold, Mischa Dieterle, Rita Loogen, and Steffen Priebe: Hierarchical Master-Worker Skeletons. In Paul Hudak and David S. Warren, editors, Practical Aspects of Declarative Languages, LNCS 4902, pages 248 - 264. Springer, 2008. Jost Berthold and Rita Loogen: Visualizing Parallel Functional Program Runs - Case Studies with the Eden Trace Viewer. In Parallel Computing: Architectures, Algorithms and Applications. Proceedings of the International Conference ParCo 2007, September 2007 Central Institute for Applied Mathematics, Jülich, Germany, 2007, NIC Series 38. Jost Berthold and Rita Loogen: Parallel coordination made explicit in a functional setting . In Zoltán Horváth and Viktória Zsók, editors, 18th Intl. Symposium on the Implementation of Functional Languages (IFL 2006), Springer LNCS 4449, Budapest, Hungary, 2006. Jost Berthold and Rita Loogen: Skeletons for Recursively Unfoldung Process Topologies , Mini-Symposium on Algorithmic Skeletons and High-Level Concepts for Parallel Programming at the Conference on Parallel Computing (ParCo) 2005, NIC Series 33.

43. Www.eecs.ucf.edu I. Introduction to Haskell. A. advertisment WHY STUDY FUNCTIONAL LANGUAGES? Programming Reuse http://www.eecs.ucf.edu/~leavens/ComS541Fall97/meeting-outlines/haskell.txt

I. Introduction to Haskell A. advertisment WHY STUDY FUNCTIONAL LANGUAGES? Programming: Reuse: Language Design: MORE REASONS TO STUDY FUNCTIONAL LANGUAGES Semantics: Typing: Reasoning: B. the problem with functional languages THE PROBLEM WITH FUNCTIONAL PROGRAMMING AND PREVIEW OF A SOLUTION Initial interpreter: eval :: Exp -> Env Val -> Val ... let v = (eval e env) ... To add a store, change the type: eval :: Exp -> Env Val -> Store -> (Val, Store) ... let (v,s) = (eval e env store) ... WITH MONADS eval :: Exp -> Env Val -> IdM -> IdM ... do v <- eval e env ... eval :: Exp -> Env Val -> StoreM -> StoreM ... do v <=, ... HASKELL INTEGERS Integer Values: + abstract values: 0, 1, -1, ... + printed: 0, 1, -1, ... Operations: + constructors: 0, 1, 2, 3, ... + functions: +, -, *, negate, abs, signum, quot, rem, div, mod, ==, /=, <- [1 ..], even e] = do e <- [1,2], > b

44. Functional Languages - Poised Solutions Functional Language Services from Poised Solutions. Functional Programmer for Hire at Poised Solutions. http://www.poisedsolutions.com/functional-languages.htm

45. Courseware: Parallel Programming Basics Introduction to parallel programming constructs-Design of Parallel solutions-Checking correctness-Tuning performance http://software.intel.com/en-us/courseware/course/category.php?id=72

46. Higher-Order And Symbolic Computation, Volume 16 Comparing Parallel Functional Languages Programming and Performance. 203251; Inge Li G rtz, Signe Reuss, Morten Heine S rensen Strong Normalization from Weak Normalization by http://dblp.uni-trier.de/db/journals/lisp/lisp16.html

Higher-Order and Symbolic Computation , Volume 16 Volume 16, Number 1-2, March-June 2003 Special Issue: Special Issue Dedicated to Bob Paige Olivier Danvy Fritz Henglein Harry G. Mairson Alberto Pettorossi Editorial: Special Issue Dedicated to Bob Paige. Bob Paige Research Retrospective. Oege de Moor David Lacey Eric Van Wyk Universal Regular Path Queries. Yanhong A. Liu Scott D. Stoller Dynamic Programming via Static Incrementalization. Elizabeth I. Leonard Constance L. Heitmeyer Program Synthesis from Formal Requirements Specifications Using APTS. Thomas W. Reps Louis B. Rall Computational Divided Differencing and Divided-Difference Arithmetics. Volume 16, Number 3, September 2003 Jonathan Ford Ian A. Mason Formal Foundations of Operational Semantics. Hans-Wolfgang Loidl Fernando Rubio Norman Scaife Kevin Hammond ... Philip W. Trinder Comparing Parallel Functional Languages: Programming and Performance. Signe Reuss Strong Normalization from Weak Normalization by Translation into the Lambda-I-Calculus. Volume 16, Number 4, December 2003 Roberto Giacobazzi Isabella Mastroeni Non-Standard Semantics for Program Slicing.

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