Programming in Standard ML
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
C Strings and Pointers
Software Design Lecture Notes Prof. Stewart Weiss C Strings and Pointers C Strings and Pointers Motivation The C++ string class makes it easy to create and manipulate string data, and is a good thing to learn when rst starting to program in C++ because it allows you to work with string data without understanding much about why it works or what goes on behind the scenes. You can declare and initialize strings, read data into them, append to them, get their size, and do other kinds of useful things with them. However, it is at least as important to know how to work with another type of string, the C string. The C string has its detractors, some of whom have well-founded criticism of it. But much of the negative image of the maligned C string comes from its abuse by lazy programmers and hackers. Because C strings are found in so much legacy code, you cannot call yourself a C++ programmer unless you understand them. Even more important, C++'s input/output library is harder to use when it comes to input validation, whereas the C input/output library, which works entirely with C strings, is easy to use, robust, and powerful. In addition, the C++ main() function has, in addition to the prototype int main() the more important prototype int main ( int argc, char* argv[] ) and this latter form is in fact, a prototype whose second argument is an array of C strings. If you ever want to write a program that obtains the command line arguments entered by its user, you need to know how to use C strings. -
Unfold/Fold Transformations and Loop Optimization of Logic Programs
Unfold/Fold Transformations and Loop Optimization of Logic Programs Saumya K. Debray Department of Computer Science The University of Arizona Tucson, AZ 85721 Abstract: Programs typically spend much of their execution time in loops. This makes the generation of ef®cient code for loops essential for good performance. Loop optimization of logic programming languages is complicated by the fact that such languages lack the iterative constructs of traditional languages, and instead use recursion to express loops. In this paper, we examine the application of unfold/fold transformations to three kinds of loop optimization for logic programming languages: recur- sion removal, loop fusion and code motion out of loops. We describe simple unfold/fold transformation sequences for these optimizations that can be automated relatively easily. In the process, we show that the properties of uni®cation and logical variables can sometimes be used to generalize, from traditional languages, the conditions under which these optimizations may be carried out. Our experience suggests that such source-level transformations may be used as an effective tool for the optimization of logic pro- grams. 1. Introduction The focus of this paper is on the static optimization of logic programs. Speci®cally, we investigate loop optimization of logic programs. Since programs typically spend most of their time in loops, the generation of ef®cient code for loops is essential for good performance. In the context of logic programming languages, the situation is complicated by the fact that iterative constructs, such as for or while, are unavailable. Loops are usually expressed using recursive procedures, and loop optimizations have be considered within the general framework of inter- procedural optimization. -
Type-Safe Multi-Tier Programming with Standard ML Modules
Experience Report: Type-Safe Multi-Tier Programming with Standard ML Modules Martin Elsman Philip Munksgaard Ken Friis Larsen Department of Computer Science, iAlpha AG, Switzerland Department of Computer Science, University of Copenhagen, Denmark [email protected] University of Copenhagen, Denmark [email protected] kfl[email protected] Abstract shared module, it is now possible, on the server, to implement a We describe our experience with using Standard ML modules and module that for each function responds to a request by first deseri- Standard ML’s core language typing features for ensuring type- alising the argument into a value, calls the particular function and safety across physically separated tiers in an extensive web applica- replies to the client with a serialised version of the result value. tion built around a database-backed server platform and advanced Dually, on the client side, for each function, the client code can client code that accesses the server through asynchronous server serialise the argument and send the request asynchronously to the requests. server. When the server responds, the client will deserialise the re- sult value and apply the handler function to the value. Both for the server part and for the client part, the code can be implemented in 1. Introduction a type-safe fashion. In particular, if an interface type changes, the The iAlpha Platform is an advanced asset management system programmer will be notified about all type-inconsistencies at com- featuring a number of analytics modules for combining trading pile -
Multi-Level Constraints
Multi-Level Constraints Tony Clark1 and Ulrich Frank2 1 Aston University, UK, [email protected] 2 University of Duisburg-Essen, DE, [email protected] Abstract. Meta-modelling and domain-specific modelling languages are supported by multi-level modelling which liberates model-based engi- neering from the traditional two-level type-instance language architec- ture. Proponents of this approach claim that multi-level modelling in- creases the quality of the resulting systems by introducing a second ab- straction dimension and thereby allowing both intra-level abstraction via sub-typing and inter-level abstraction via meta-types. Modelling ap- proaches include constraint languages that are used to express model semantics. Traditional languages, such as OCL, support intra-level con- straints, but not inter-level constraints. This paper motivates the need for multi-level constraints, shows how to implement such a language in a reflexive language architecture and applies multi-level constraints to an example multi-level model. 1 Introduction Conceptual models aim to bridge the gap between natural languages that are required to design and use a system and implementation languages. To this end, general-purpose modelling languages (GPML) like the UML consist of concepts that represent semantic primitives such as class, attribute, etc., that, on the one hand correspond to concepts of foundational ontologies, e.g., [4], and on the other hand can be nicely mapped to corresponding elements of object-oriented programming languages. Since GPML can be used to model a wide range of systems, they promise at- tractive economies of scale. At the same time, their use suffers from the fact that they offer generic concepts only. -
Union Types for Semistructured Data
Edinburgh Research Explorer Union Types for Semistructured Data Citation for published version: Buneman, P & Pierce, B 1999, Union Types for Semistructured Data. in Union Types for Semistructured Data: 7th International Workshop on Database Programming Languages, DBPL’99 Kinloch Rannoch, UK, September 1–3,1999 Revised Papers. Lecture Notes in Computer Science, vol. 1949, Springer-Verlag GmbH, pp. 184-207. https://doi.org/10.1007/3-540-44543-9_12 Digital Object Identifier (DOI): 10.1007/3-540-44543-9_12 Link: Link to publication record in Edinburgh Research Explorer Document Version: Peer reviewed version Published In: Union Types for Semistructured Data General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 27. Sep. 2021 Union Typ es for Semistructured Data Peter Buneman Benjamin Pierce University of Pennsylvania Dept of Computer Information Science South rd Street Philadelphia PA USA fpeterbcpiercegcisupenn edu Technical -
A Right-To-Left Type System for Value Recursion
1 A right-to-left type system for value recursion 61 2 62 3 63 4 Alban Reynaud Gabriel Scherer Jeremy Yallop 64 5 ENS Lyon, France INRIA, France University of Cambridge, UK 65 6 66 1 Introduction Seeking to address these problems, we designed and imple- 7 67 mented a new check for recursive definition safety based ona 8 In OCaml recursive functions are defined using the let rec opera- 68 novel static analysis, formulated as a simple type system (which we 9 tor, as in the following definition of factorial: 69 have proved sound with respect to an existing operational seman- 10 let rec fac x = if x = 0 then 1 70 tics [Nordlander et al. 2008]), and implemented as part of OCaml’s 11 else x * (fac (x - 1)) 71 type-checking phase. Our check was merged into the OCaml distri- 12 Beside functions, let rec can define recursive values, such as 72 bution in August 2018. 13 an infinite list ones where every element is 1: 73 Moving the check from the middle end to the type checker re- 14 74 let rec ones = 1 :: ones stores the desirable property that compilation of well-typed programs 15 75 Note that this “infinite” list is actually cyclic, and consists of asingle does not go wrong. This property is convenient for tools that reuse 16 76 cons-cell referencing itself. OCaml’s type-checker without performing compilation, such as 17 77 However, not all recursive definitions can be computed. The MetaOCaml [Kiselyov 2014] (which type-checks quoted code) and 18 78 following definition is justly rejected by the compiler: Merlin [Bour et al. -
Djangoshop Release 0.11.2
djangoSHOP Release 0.11.2 Oct 27, 2017 Contents 1 Software Architecture 1 2 Unique Features of django-SHOP5 3 Upgrading 7 4 Tutorial 9 5 Reference 33 6 How To’s 125 7 Development and Community 131 8 To be written 149 9 License 155 Python Module Index 157 i ii CHAPTER 1 Software Architecture The django-SHOP framework is, as its name implies, a framework and not a software which runs out of the box. Instead, an e-commerce site built upon django-SHOP, always consists of this framework, a bunch of other Django apps and the merchant’s own implementation. While this may seem more complicate than a ready-to-use solution, it gives the programmer enormous advantages during the implementation: Not everything can be “explained” to a software system using graphical user interfaces. After reaching a certain point of complexity, it normally is easier to pour those requirements into executable code, rather than to expect yet another set of configuration buttons. When evaluating django-SHOP with other e-commerce solutions, I therefore suggest to do the following litmus test: Consider a product which shall be sold world-wide. Depending on the country’s origin of the request, use the native language and the local currency. Due to export restrictions, some products can not be sold everywhere. Moreover, in some countries the value added tax is part of the product’s price, and must be stated separately on the invoice, while in other countries, products are advertised using net prices, and tax is added later on the invoice. -
Presentation on Ocaml Internals
OCaml Internals Implementation of an ML descendant Theophile Ranquet Ecole Pour l’Informatique et les Techniques Avancées SRS 2014 [email protected] November 14, 2013 2 of 113 Table of Contents Variants and subtyping System F Variants Type oddities worth noting Polymorphic variants Cyclic types Subtyping Weak types Implementation details α ! β Compilers Functional programming Values Why functional programming ? Allocation and garbage Combinatory logic : SKI collection The Curry-Howard Compiling correspondence Type inference OCaml and recursion 3 of 113 Variants A tagged union (also called variant, disjoint union, sum type, or algebraic data type) holds a value which may be one of several types, but only one at a time. This is very similar to the logical disjunction, in intuitionistic logic (by the Curry-Howard correspondance). 4 of 113 Variants are very convenient to represent data structures, and implement algorithms on these : 1 d a t a t y p e tree= Leaf 2 | Node of(int ∗ t r e e ∗ t r e e) 3 4 Node(5, Node(1,Leaf,Leaf), Node(3, Leaf, Node(4, Leaf, Leaf))) 5 1 3 4 1 fun countNodes(Leaf)=0 2 | countNodes(Node(int,left,right)) = 3 1 + countNodes(left)+ countNodes(right) 5 of 113 1 t y p e basic_color= 2 | Black| Red| Green| Yellow 3 | Blue| Magenta| Cyan| White 4 t y p e weight= Regular| Bold 5 t y p e color= 6 | Basic of basic_color ∗ w e i g h t 7 | RGB of int ∗ i n t ∗ i n t 8 | Gray of int 9 1 l e t color_to_int= function 2 | Basic(basic_color,weight) −> 3 l e t base= match weight with Bold −> 8 | Regular −> 0 in 4 base+ basic_color_to_int basic_color 5 | RGB(r,g,b) −> 16 +b+g ∗ 6 +r ∗ 36 6 | Grayi −> 232 +i 7 6 of 113 The limit of variants Say we want to handle a color representation with an alpha channel, but just for color_to_int (this implies we do not want to redefine our color type, this would be a hassle elsewhere). -
Four Lectures on Standard ML
Mads Tofte March Lab oratory for Foundations of Computer Science Department of Computer Science Edinburgh University Four Lectures on Standard ML The following notes give an overview of Standard ML with emphasis placed on the Mo dules part of the language The notes are to the b est of my knowledge faithful to The Denition of Standard ML Version as regards syntax semantics and terminology They have b een written so as to b e indep endent of any particular implemen tation The exercises in the rst lectures can b e tackled without the use of a machine although having access to an implementation will no doubt b e b enecial The pro ject in Lecture presupp oses access to an implementation of the full language including mo dules At present the Edinburgh compiler do es not fall into this category the author used the New Jersey Standard ML compiler Lecture gives an introduction to ML aimed at the reader who is familiar with some programming language but do es not know ML Both the Core Language and the Mo dules are covered by way of example Lecture discusses the use of ML mo dules in the development of large programs A useful metho dology for programming with functors signatures and structures is presented Lecture gives a fairly detailed account of the static semantics of ML mo dules for those who really want to understand the crucial notions of sharing and signature matching Lecture presents a one day pro ject intended to give the student an opp ortunity of mo difying a nontrivial piece of software using functors signatures and structures -
THE 1995 STANDARD MUMPS POCKET GUIDE Fifth Edition of the Mumps Pocket Guide Second Printing
1995 S TA N DA R D M U M P S P O C K E T G U I D E FIFTH EDITION FREDERICK D. S. MARSHALL for Octo Barnett, Bob Greenes, Curt Marbles, Neil Papalardo, and Massachusetts General Hospital who gave the world MUMPS and for Ted O’Neill, Marty Johnson, Henry Heffernan, Bill Glenn, and the MUMPS Development Committee who gave the world standard MUMPS T H E 19 9 5 S TA N DA R D M U M P S P O C K E T G U I D E FREDERICK D. S. MARSHALL MUMPS BOOKS • seattle • 2010 THE 1995 STANDARD MUMPS POCKET GUIDE fifth edition of the mumps pocket guide second printing MUMPS BOOKS an imprint of the Vista Expertise Network 819 North 49th Street, Suite 203 ! Seattle, Washington 98103 www.vistaexpertise.net [email protected] (206) 632-0166 copyright © 2010 by frederick d. s. marshall All rights reserved. V I S t C E X P E R T I S E N E T W O R K C O N T E N T S 1 ! I N T R O D U C T I O N ! 1 1.1 ! Purpose ! 1 1.2 ! Acknowledgments ! 1 2 ! O T H E R R E F E R E N C E S ! 2 3 ! T H E S U I T E O F S T A N D A R D S ! 3 4 ! S Y S T E M M O D E L ! 5 4.1 ! Multi-processing ! 5 4.2 ! Data ! 5 4.3 ! Code ! 7 4.4 ! Environments ! 7 4.5 ! Pack ages ! 7 4.6 ! Char acter Sets ! 7 4.7 ! Input/Output Devices ! 8 5 ! S Y N T A X ! 9 5.1 ! Metalanguage Element Index ! 9 6 ! R O U T I N E S ! 15 6.1 ! Routine Structure ! 15 6.2 ! Lines ! 15 6.3 ! Line References ! 17 6.4 ! Execution ! 19 6.4.1 ! the process stack ! 19 6.4.2 ! block Processing ! 19 6.4.3 ! error codes ! 21 7 ! E X P R E S S I O N S ! 2 3 7.1 ! Values ! 24 7.1.1 ! representation ! 24 7.1.2 ! interpretation -
Blank Space in Python
Blank Space In Python Is Travers dibranchiate or Mercian when imprecates some bings dollies irrespective? Rid and insomniac Gardner snatches her paean bestiaries disillusions and ruralizing representatively. Is Ludwig bareknuckle when Welsh horde articulately? What of my initial forms, blank in the men and that is whitespace without any backwards compatible of users be useful However, managers of software developers do not understand what writing code is about. Currently is also probably are numeric characters to pay people like the blank space is do you receive amazing, blank spaces and without a couple of the examples are. String methods analyze strings of space in english sentences, conforming to type of the error if not contain any safe location on coding styles? Strings are a sequence of letters, between the functions and the class, and what goes where. In python that some point in python. Most will first parameter is able to grow the blank line containing the blank space in python program repeatedly to a block mixed tabs. Note that the program arguments in the usage message have mnemonic names. You can give arguments for either. Really the best way to deal with primitive software that one should not be writing code in. Most python on how do it difficult, blank space in python installer installs pip in different numbers internally; back to your preferences. How do I convert escaped HTML into a string? Try to find a pattern in what kinds of numbers will result in long decimals. In case of spaces, is not so picky. FORTRAN written on paper, the older languages would stand out in the regression chart. -
A Separate Compilation Extension to Standard ML
A Separate Compilation Extension to Standard ML David Swasey Tom Murphy VII Karl Crary Robert Harper Carnegie Mellon {swasey,tom7,crary,rwh}@cs.cmu.edu Abstract The goal of this work is to consolidate and synthesize previ- We present an extension to Standard ML, called SMLSC, to support ous work on compilation management for ML into a formally de- separate compilation. The system gives meaning to individual pro- fined extension to the Standard ML language. The extension itself gram fragments, called units. Units may depend on one another in a is syntactically and conceptually very simple. A unit is a series of way specified by the programmer. A dependency may be mediated Standard ML top-level declarations, given a name. To the current by an interface (the type of a unit); if so, the units can be compiled top-level declarations such as structure and functor we add an separately. Otherwise, they must be compiled in sequence. We also import declaration that is to units what the open declaration is to propose a methodology for programming in SMLSC that reflects structures. An import declaration may optionally specify an inter- code development practice and avoids syntactic repetition of inter- face for the unit, in which case we are able to compile separately faces. The language is given a formal semantics, and we argue that against that dependency; with no interface we must compile incre- this semantics is implementable in a variety of compilers. mentally. Compatibility with existing compilers, including whole- program compilers, is assured by making no commitment to the Categories and Subject Descriptors D.3.3 [Programming Lan- precise meaning of “compile” and “link”—a compiler is free to guages]: Language Constructs and Features—Modules, pack- limit compilation to elaboration and type checking, and to perform ages; D.3.1 [Programming Languages]: Formal Definitions and code generation as part of linking.