APL-The Language Debugging Capabilities, Entirely in APL Terms (No Core Symbol Denotes an APL Function Named' 'Compress," Dumps Or Other Machine-Related Details)
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Super Family
Super Family (Chaim Freedman, Petah Tikvah, Israel, September 2008) Yehoash (Heibish/Gevush) Super, born c.1760, died before 1831 in Latvia. He married unknown. I. Shmuel Super, born 1781,1 died by 1855 in Lutzin (now Ludza), Latvia,2 occupation alcohol trader. Appears in a list from 1837 of tax litigants who were alcohol traders in Lutzin. (1) He married Brokha ?, born 1781 in Lutzin (now Ludza), Latvia,3 died before 1831 in Lutzin (now Ludza), Latvia.3 (2) He married Elka ?, born 1794.4 A. Payka Super, (daughter of Shmuel Super and Brokha ?) born 1796/1798 in Lutzin (now Ludza), Latvia,3 died 1859 in Lutzin (now Ludza), Latvia.5 She married Yaakov-Keifman (Kivka) Super, born 1798,6,3 (son of Sholom "Super" ?) died 1874 in Lutzin (now Ludza), Latvia.7 Yaakov-Keifman: Oral tradition related by his descendants claims that Koppel's surname was actually Weinstock and that he married into the Super family. The name change was claimed to have taken place to evade military service. But this story seems to be invalid as all census records for him and his sons use the name Super. 1. Moshe Super, born 1828 in Lutzin (now Ludza), Latvia.8 He married Sara Goda ?, born 1828.8 a. Bentsion Super, born 1851 in Lutzin (now Ludza), Latvia.9 He married Khana ?, born 1851.9 b. Payka Super, born 1854 in Lutzin (now Ludza), Latvia.10 c. Rassa Super, born 1857 in Lutzin (now Ludza), Latvia.11 d. Riva Super, born 1860 in Lutzin (now Ludza), Latvia.12 e. Mushke Super, born 1865 in Lutzin (now Ludza), Latvia.13 f. -
An Array-Oriented Language with Static Rank Polymorphism
An array-oriented language with static rank polymorphism Justin Slepak, Olin Shivers, and Panagiotis Manolios Northeastern University fjrslepak,shivers,[email protected] Abstract. The array-computational model pioneered by Iverson's lan- guages APL and J offers a simple and expressive solution to the \von Neumann bottleneck." It includes a form of rank, or dimensional, poly- morphism, which renders much of a program's control structure im- plicit by lifting base operators to higher-dimensional array structures. We present the first formal semantics for this model, along with the first static type system that captures the full power of the core language. The formal dynamic semantics of our core language, Remora, illuminates several of the murkier corners of the model. This allows us to resolve some of the model's ad hoc elements in more general, regular ways. Among these, we can generalise the model from SIMD to MIMD computations, by extending the semantics to permit functions to be lifted to higher- dimensional arrays in the same way as their arguments. Our static semantics, a dependent type system of carefully restricted power, is capable of describing array computations whose dimensions cannot be determined statically. The type-checking problem is decidable and the type system is accompanied by the usual soundness theorems. Our type system's principal contribution is that it serves to extract the implicit control structure that provides so much of the language's expres- sive power, making this structure explicitly apparent at compile time. 1 The Promise of Rank Polymorphism Behind every interesting programming language is an interesting model of com- putation. -
BUGS Code for Item Response Theory
JSS Journal of Statistical Software August 2010, Volume 36, Code Snippet 1. http://www.jstatsoft.org/ BUGS Code for Item Response Theory S. McKay Curtis University of Washington Abstract I present BUGS code to fit common models from item response theory (IRT), such as the two parameter logistic model, three parameter logisitic model, graded response model, generalized partial credit model, testlet model, and generalized testlet models. I demonstrate how the code in this article can easily be extended to fit more complicated IRT models, when the data at hand require a more sophisticated approach. Specifically, I describe modifications to the BUGS code that accommodate longitudinal item response data. Keywords: education, psychometrics, latent variable model, measurement model, Bayesian inference, Markov chain Monte Carlo, longitudinal data. 1. Introduction In this paper, I present BUGS (Gilks, Thomas, and Spiegelhalter 1994) code to fit several models from item response theory (IRT). Several different software packages are available for fitting IRT models. These programs include packages from Scientific Software International (du Toit 2003), such as PARSCALE (Muraki and Bock 2005), BILOG-MG (Zimowski, Mu- raki, Mislevy, and Bock 2005), MULTILOG (Thissen, Chen, and Bock 2003), and TESTFACT (Wood, Wilson, Gibbons, Schilling, Muraki, and Bock 2003). The Comprehensive R Archive Network (CRAN) task view \Psychometric Models and Methods" (Mair and Hatzinger 2010) contains a description of many different R packages that can be used to fit IRT models in the R computing environment (R Development Core Team 2010). Among these R packages are ltm (Rizopoulos 2006) and gpcm (Johnson 2007), which contain several functions to fit IRT models using marginal maximum likelihood methods, and eRm (Mair and Hatzinger 2007), which contains functions to fit several variations of the Rasch model (Fischer and Molenaar 1995). -
Compendium of Technical White Papers
COMPENDIUM OF TECHNICAL WHITE PAPERS Compendium of Technical White Papers from Kx Technical Whitepaper Contents Machine Learning 1. Machine Learning in kdb+: kNN classification and pattern recognition with q ................................ 2 2. An Introduction to Neural Networks with kdb+ .......................................................................... 16 Development Insight 3. Compression in kdb+ ................................................................................................................. 36 4. Kdb+ and Websockets ............................................................................................................... 52 5. C API for kdb+ ............................................................................................................................ 76 6. Efficient Use of Adverbs ........................................................................................................... 112 Optimization Techniques 7. Multi-threading in kdb+: Performance Optimizations and Use Cases ......................................... 134 8. Kdb+ tick Profiling for Throughput Optimization ....................................................................... 152 9. Columnar Database and Query Optimization ............................................................................ 166 Solutions 10. Multi-Partitioned kdb+ Databases: An Equity Options Case Study ............................................. 192 11. Surveillance Technologies to Effectively Monitor Algo and High Frequency Trading .................. -
A Quick Reference to C Programming Language
A Quick Reference to C Programming Language Structure of a C Program #include(stdio.h) /* include IO library */ #include... /* include other files */ #define.. /* define constants */ /* Declare global variables*/) (variable type)(variable list); /* Define program functions */ (type returned)(function name)(parameter list) (declaration of parameter types) { (declaration of local variables); (body of function code); } /* Define main function*/ main ((optional argc and argv arguments)) (optional declaration parameters) { (declaration of local variables); (body of main function code); } Comments Format: /*(body of comment) */ Example: /*This is a comment in C*/ Constant Declarations Format: #define(constant name)(constant value) Example: #define MAXIMUM 1000 Type Definitions Format: typedef(datatype)(symbolic name); Example: typedef int KILOGRAMS; Variables Declarations: Format: (variable type)(name 1)(name 2),...; Example: int firstnum, secondnum; char alpha; int firstarray[10]; int doublearray[2][5]; char firststring[1O]; Initializing: Format: (variable type)(name)=(value); Example: int firstnum=5; Assignments: Format: (name)=(value); Example: firstnum=5; Alpha='a'; Unions Declarations: Format: union(tag) {(type)(member name); (type)(member name); ... }(variable name); Example: union demotagname {int a; float b; }demovarname; Assignment: Format: (tag).(member name)=(value); demovarname.a=1; demovarname.b=4.6; Structures Declarations: Format: struct(tag) {(type)(variable); (type)(variable); ... }(variable list); Example: struct student {int -
Lecture 2: Introduction to C Programming Language [email protected]
CSCI-UA 201 Joanna Klukowska Lecture 2: Introduction to C Programming Language [email protected] Lecture 2: Introduction to C Programming Language Notes include some materials provided by Andrew Case, Jinyang Li, Mohamed Zahran, and the textbooks. Reading materials Chapters 1-6 in The C Programming Language, by B.W. Kernighan and Dennis M. Ritchie Section 1.2 and Aside on page 4 in Computer Systems, A Programmer’s Perspective by R.E. Bryant and D.R. O’Hallaron Contents 1 Intro to C and Unix/Linux 3 1.1 Why C?............................................................3 1.2 C vs. Java...........................................................3 1.3 Code Development Process (Not Only in C).........................................4 1.4 Basic Unix Commands....................................................4 2 First C Program and Stages of Compilation 6 2.1 Writing and running hello world in C.............................................6 2.2 Hello world line by line....................................................7 2.3 What really happens when we compile a program?.....................................8 3 Basics of C 9 3.1 Data types (primitive types)..................................................9 3.2 Using printf to print different data types.........................................9 3.3 Control flow.......................................................... 10 3.4 Functions........................................................... 11 3.5 Variable scope........................................................ 12 3.6 Header files......................................................... -
APL Literature Review
APL Literature Review Roy E. Lowrance February 22, 2009 Contents 1 Falkoff and Iverson-1968: APL1 3 2 IBM-1994: APL2 8 2.1 APL2 Highlights . 8 2.2 APL2 Primitive Functions . 12 2.3 APL2 Operators . 18 2.4 APL2 Concurrency Features . 19 3 Dyalog-2008: Dyalog APL 20 4 Iverson-1987: Iverson's Dictionary for APL 21 5 APL Implementations 21 5.1 Saal and Weiss-1975: Static Analysis of APL1 Programs . 21 5.2 Breed and Lathwell-1968: Implementation of the Original APLn360 25 5.3 Falkoff and Orth-1979: A BNF Grammar for APL1 . 26 5.4 Girardo and Rollin-1987: Parsing APL with Yacc . 27 5.5 Tavera and other-1987, 1998: IL . 27 5.6 Brown-1995: Rationale for APL2 Syntax . 29 5.7 Abrams-1970: An APL Machine . 30 5.8 Guibas and Wyatt-1978: Optimizing Interpretation . 31 5.9 Weiss and Saal-1981: APL Syntax Analysis . 32 5.10 Weigang-1985: STSC's APL Compiler . 33 5.11 Ching-1986: APL/370 Compiler . 33 5.12 Ching and other-1989: APL370 Prototype Compiler . 34 5.13 Driscoll and Orth-1986: Compile APL2 to FORTRAN . 35 5.14 Grelck-1999: Compile APL to Single Assignment C . 36 6 Imbed APL in Other Languages 36 6.1 Burchfield and Lipovaca-2002: APL Arrays in Java . 36 7 Extensions to APL 37 7.1 Brown and Others-2000: Object-Oriented APL . 37 1 8 APL on Parallel Computers 38 8.1 Willhoft-1991: Most APL2 Primitives Can Be Parallelized . 38 8.2 Bernecky-1993: APL Can Be Parallelized . -
A Tutorial Introduction to the Language B
A TUTORIAL INTRODUCTION TO THE LANGUAGE B B. W. Kernighan Bell Laboratories Murray Hill, New Jersey 1. Introduction B is a new computer language designed and implemented at Murray Hill. It runs and is actively supported and documented on the H6070 TSS system at Murray Hill. B is particularly suited for non-numeric computations, typified by system programming. These usually involve many complex logical decisions, computations on integers and fields of words, especially charac- ters and bit strings, and no floating point. B programs for such operations are substantially easier to write and understand than GMAP programs. The generated code is quite good. Implementation of simple TSS subsystems is an especially good use for B. B is reminiscent of BCPL [2] , for those who can remember. The original design and implementation are the work of K. L. Thompson and D. M. Ritchie; their original 6070 version has been substantially improved by S. C. Johnson, who also wrote the runtime library. This memo is a tutorial to make learning B as painless as possible. Most of the features of the language are mentioned in passing, but only the most important are stressed. Users who would like the full story should consult A User’s Reference to B on MH-TSS, by S. C. Johnson [1], which should be read for details any- way. We will assume that the user is familiar with the mysteries of TSS, such as creating files, text editing, and the like, and has programmed in some language before. Throughout, the symbolism (->n) implies that a topic will be expanded upon in section n of this manual. -
Application and Interpretation
Programming Languages: Application and Interpretation Shriram Krishnamurthi Brown University Copyright c 2003, Shriram Krishnamurthi This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License. If you create a derivative work, please include the version information below in your attribution. This book is available free-of-cost from the author’s Web site. This version was generated on 2007-04-26. ii Preface The book is the textbook for the programming languages course at Brown University, which is taken pri- marily by third and fourth year undergraduates and beginning graduate (both MS and PhD) students. It seems very accessible to smart second year students too, and indeed those are some of my most successful students. The book has been used at over a dozen other universities as a primary or secondary text. The book’s material is worth one undergraduate course worth of credit. This book is the fruit of a vision for teaching programming languages by integrating the “two cultures” that have evolved in its pedagogy. One culture is based on interpreters, while the other emphasizes a survey of languages. Each approach has significant advantages but also huge drawbacks. The interpreter method writes programs to learn concepts, and has its heart the fundamental belief that by teaching the computer to execute a concept we more thoroughly learn it ourselves. While this reasoning is internally consistent, it fails to recognize that understanding definitions does not imply we understand consequences of those definitions. For instance, the difference between strict and lazy evaluation, or between static and dynamic scope, is only a few lines of interpreter code, but the consequences of these choices is enormous. -
Command $Line; Done
http://xkcd.com/208/ >0 TGCAGGTATATCTATTAGCAGGTTTAATTTTGCCTGCACTTGGTTGGGTACATTATTTTAAGTGTATTTGACAAG >1 TGCAGGTTGTTGTTACTCAGGTCCAGTTCTCTGAGACTGGAGGACTGGGAGCTGAGAACTGAGGACAGAGCTTCA >2 TGCAGGGCCGGTCCAAGGCTGCATGAGGCCTGGGGCAGAATCTGACCTAGGGGCCCCTCTTGCTGCTAAAACCAT >3 TGCAGGATCTGCTGCACCATTAACCAGACAGAAATGGCAGTTTTATACAAGTTATTATTCTAATTCAATAGCTGA >4 TGCAGGGGTCAAATACAGCTGTCAAAGCCAGACTTTGAGCACTGCTAGCTGGCTGCAACACCTGCACTTAACCTC cat seqs.fa PIPE grep ACGT TGCAGGTATATCTATTAGCAGGTTTAATTTTGCCTGCACTTGGTTGGGTACATTATTTTAAGTGTATTTGACAAG >1 TGCAGGTTGTTGTTACTCAGGTCCAGTTCTCTGAGACTGGAGGACTGGGAGCTGAGAACTGAGGACAGAGCTTCA >2 TGCAGGGCCGGTCCAAGGCTGCATGAGGCCTGGGGCAGAATCTGACCTAGGGGCCCCTCTTGCTGCTAAAACCAT >3 TGCAGGATCTGCTGCACCATTAACCAGACAGAAATGGCAGTTTTATACAAGTTATTATTCTAATTCAATAGCTGA >4 TGCAGGGGTCAAATACAGCTGTCAAAGCCAGACTTTGAGCACTGCTAGCTGGCTGCAACACCTGCACTTAACCTC cat seqs.fa Does PIPE “>0” grep ACGT contain “ACGT”? Yes? No? Output NULL >1 TGCAGGTTGTTGTTACTCAGGTCCAGTTCTCTGAGACTGGAGGACTGGGAGCTGAGAACTGAGGACAGAGCTTCA >2 TGCAGGGCCGGTCCAAGGCTGCATGAGGCCTGGGGCAGAATCTGACCTAGGGGCCCCTCTTGCTGCTAAAACCAT >3 TGCAGGATCTGCTGCACCATTAACCAGACAGAAATGGCAGTTTTATACAAGTTATTATTCTAATTCAATAGCTGA >4 TGCAGGGGTCAAATACAGCTGTCAAAGCCAGACTTTGAGCACTGCTAGCTGGCTGCAACACCTGCACTTAACCTC cat seqs.fa Does PIPE “TGCAGGTATATCTATTAGCAGGTTTAATTTTGCCTGCACTTG...G” grep ACGT contain “ACGT”? Yes? No? Output NULL TGCAGGTTGTTGTTACTCAGGTCCAGTTCTCTGAGACTGGAGGACTGGGAGCTGAGAACTGAGGACAGAGCTTCA >2 TGCAGGGCCGGTCCAAGGCTGCATGAGGCCTGGGGCAGAATCTGACCTAGGGGCCCCTCTTGCTGCTAAAACCAT >3 TGCAGGATCTGCTGCACCATTAACCAGACAGAAATGGCAGTTTTATACAAGTTATTATTCTAATTCAATAGCTGA -
The C Programming Language
The C programming Language The C programming Language By Brian W. Kernighan and Dennis M. Ritchie. Published by Prentice-Hall in 1988 ISBN 0-13-110362-8 (paperback) ISBN 0-13-110370-9 Contents ● Preface ● Preface to the first edition ● Introduction 1. Chapter 1: A Tutorial Introduction 1. Getting Started 2. Variables and Arithmetic Expressions 3. The for statement 4. Symbolic Constants 5. Character Input and Output 1. File Copying 2. Character Counting 3. Line Counting 4. Word Counting 6. Arrays 7. Functions 8. Arguments - Call by Value 9. Character Arrays 10. External Variables and Scope 2. Chapter 2: Types, Operators and Expressions 1. Variable Names 2. Data Types and Sizes 3. Constants 4. Declarations http://freebooks.by.ru/view/CProgrammingLanguage/kandr.html (1 of 5) [5/15/2002 10:12:59 PM] The C programming Language 5. Arithmetic Operators 6. Relational and Logical Operators 7. Type Conversions 8. Increment and Decrement Operators 9. Bitwise Operators 10. Assignment Operators and Expressions 11. Conditional Expressions 12. Precedence and Order of Evaluation 3. Chapter 3: Control Flow 1. Statements and Blocks 2. If-Else 3. Else-If 4. Switch 5. Loops - While and For 6. Loops - Do-While 7. Break and Continue 8. Goto and labels 4. Chapter 4: Functions and Program Structure 1. Basics of Functions 2. Functions Returning Non-integers 3. External Variables 4. Scope Rules 5. Header Files 6. Static Variables 7. Register Variables 8. Block Structure 9. Initialization 10. Recursion 11. The C Preprocessor 1. File Inclusion 2. Macro Substitution 3. Conditional Inclusion 5. Chapter 5: Pointers and Arrays 1. -
Kenneth E. Iverson
Kenneth E. Iverson Born December 17, 1920, Camrose, Alberta, Canada; with Adin Falkoff, inventor and implementer of the programming language APL. Education: BA, mathematics, Queen's University at Kingston, Ont., 1950; MA, mathematics, Harvard University, 1951; PhD, applied mathematics, Harvard University, 1954. Professional Experience: assistant professor, Harvard University, 1955-1960; research division, IBM Corp., 1960-1980; I.P. Sharp Associates, 1980-1987. Honors and Awards: IBM Fellow, 1970; AFIPS Harry Goode Award, 1975; ACM Turing Award, 1979; IEEE Computer Pioneer Award, 1982; National Medal of Technology, 1991; member, National Academy of Engineering. Iverson has been one of those lucky individuals who has been able to start his career with a success and for over 35 years build on that success by adding to it, enhancing it, and seeing it develop into a successful commercial property. His book A Programming Language set the stage for a concept whose peculiar character set would have appeared to eliminate it from consideration for implementation on any computer. Adin Falkoff is credited by Iverson for picking the name APL for the programming language implementation, and the introduction of the IBM “golf-ball” typewriter, with the replacement typehead, which provided the character set to represent programs. The programming language became the language of enthusiasts (some would say fanatics) and the challenge of minimalists to contain as much processing as possible within one line of code. APL has outlived many other languages and its enthusiasts range from elementary school students to research scientists. BIBLIOGRAPHY Biographical Falkoff, Adin D., and Kenneth E. Iverson, “The Evolution of APL,” in Wexelblat, Richard L., ed., History of Programming Languages, Academic Press, New York, 1981, Chapter 14.