Practical Optional Types for Clojure
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Homework 2: Reflection and Multiple Dispatch in Smalltalk
Com S 541 — Programming Languages 1 October 2, 2002 Homework 2: Reflection and Multiple Dispatch in Smalltalk Due: Problems 1 and 2, September 24, 2002; problems 3 and 4, October 8, 2002. This homework can either be done individually or in teams. Its purpose is to familiarize you with Smalltalk’s reflection facilities and to help learn about other issues in OO language design. Don’t hesitate to contact the staff if you are not clear about what to do. In this homework, you will adapt the “multiple dispatch as dispatch on tuples” approach, origi- nated by Leavens and Millstein [1], to Smalltalk. To do this you will have to read their paper and then do the following. 1. (30 points) In a new category, Tuple-Smalltalk, add a class Tuple, which has indexed instance variables. Design this type to provide the necessary methods for working with dispatch on tuples, for example, we’d like to have access to the tuple of classes of the objects in a given tuple. Some of these methods will depend on what’s below. Also design methods so that tuples can be used as a data structure (e.g., to pass multiple arguments and return multiple results). 2. (50 points) In the category, Tuple-Smalltalk, design other classes to hold the behavior that will be declared for tuples. For example, you might want something analogous to a method dictionary and other things found in the class Behavior or ClassDescription. It’s worth studying those classes to see what can be adapted to our purposes. -
TAMING the MERGE OPERATOR a Type-Directed Operational Semantics Approach
Technical Report, Department of Computer Science, the University of Hong Kong, Jan 2021. 1 TAMING THE MERGE OPERATOR A Type-directed Operational Semantics Approach XUEJING HUANG JINXU ZHAO BRUNO C. D. S. OLIVEIRA The University of Hong Kong (e-mail: fxjhuang, jxzhao, [email protected]) Abstract Calculi with disjoint intersection types support a symmetric merge operator with subtyping. The merge operator generalizes record concatenation to any type, enabling expressive forms of object composition, and simple solutions to hard modularity problems. Unfortunately, recent calculi with disjoint intersection types and the merge operator lack a (direct) operational semantics with expected properties such as determinism and subject reduction, and only account for terminating programs. This paper proposes a type-directed operational semantics (TDOS) for calculi with intersection types and a merge operator. We study two variants of calculi in the literature. The first calculus, called li, is a variant of a calculus presented by Oliveira et al. (2016) and closely related to another calculus by Dunfield (2014). Although Dunfield proposes a direct small-step semantics for her calcu- lus, her semantics lacks both determinism and subject reduction. Using our TDOS we obtain a direct + semantics for li that has both properties. The second calculus, called li , employs the well-known + subtyping relation of Barendregt, Coppo and Dezani-Ciancaglini (BCD). Therefore, li extends the more basic subtyping relation of li, and also adds support for record types and nested composition (which enables recursive composition of merged components). To fully obtain determinism, both li + and li employ a disjointness restriction proposed in the original li calculus. -
Julia: a Fresh Approach to Numerical Computing
RSDG @ UCL Julia: A Fresh Approach to Numerical Computing Mosè Giordano @giordano [email protected] Knowledge Quarter Codes Tech Social October 16, 2019 Julia’s Facts v1.0.0 released in 2018 at UCL • Development started in 2009 at MIT, first • public release in 2012 Julia co-creators won the 2019 James H. • Wilkinson Prize for Numerical Software Julia adoption is growing rapidly in • numerical optimisation, differential equations, machine learning, differentiable programming It is used and taught in several universities • (https://julialang.org/teaching/) Mosè Giordano (RSDG @ UCL) Julia: A Fresh Approach to Numerical Computing October 16, 2019 2 / 29 Julia on Nature Nature 572, 141-142 (2019). doi: 10.1038/d41586-019-02310-3 Mosè Giordano (RSDG @ UCL) Julia: A Fresh Approach to Numerical Computing October 16, 2019 3 / 29 Solving the Two-Language Problem: Julia Multiple dispatch • Dynamic type system • Good performance, approaching that of statically-compiled languages • JIT-compiled scripts • User-defined types are as fast and compact as built-ins • Lisp-like macros and other metaprogramming facilities • No need to vectorise: for loops are fast • Garbage collection: no manual memory management • Interactive shell (REPL) for exploratory work • Call C and Fortran functions directly: no wrappers or special APIs • Call Python functions: use the PyCall package • Designed for parallelism and distributed computation • Mosè Giordano (RSDG @ UCL) Julia: A Fresh Approach to Numerical Computing October 16, 2019 4 / 29 Multiple Dispatch using DifferentialEquations -
Concepts in Programming Languages Practicalities
Concepts in Programming Languages Practicalities I Course web page: Alan Mycroft1 www.cl.cam.ac.uk/teaching/1617/ConceptsPL/ with lecture slides, exercise sheet and reading material. These slides play two roles – both “lecture notes" and “presentation material”; not every slide will be lectured in Computer Laboratory detail. University of Cambridge I There are various code examples (particularly for 2016–2017 (Easter Term) JavaScript and Java applets) on the ‘materials’ tab of the course web page. I One exam question. www.cl.cam.ac.uk/teaching/1617/ConceptsPL/ I The syllabus and course has changed somewhat from that of 2015/16. I would be grateful for comments on any remaining ‘rough edges’, and for views on material which is either over- or under-represented. 1Acknowledgement: various slides are based on Marcelo Fiore’s 2013/14 course. Alan Mycroft Concepts in Programming Languages 1 / 237 Alan Mycroft Concepts in Programming Languages 2 / 237 Main books Context: so many programming languages I J. C. Mitchell. Concepts in programming languages. Cambridge University Press, 2003. Peter J. Landin: “The Next 700 Programming Languages”, I T.W. Pratt and M. V.Zelkowitz. Programming Languages: CACM (published in 1966!). Design and implementation (3RD EDITION). Some programming-language ‘family trees’ (too big for slide): Prentice Hall, 1999. http://www.oreilly.com/go/languageposter http://www.levenez.com/lang/ ? M. L. Scott. Programming language pragmatics http://rigaux.org/language-study/diagram.html (4TH EDITION). http://www.rackspace.com/blog/ Elsevier, 2016. infographic-evolution-of-computer-languages/ I R. Harper. Practical Foundations for Programming Plan of this course: pick out interesting programming-language Languages. -
Characteristics of Mathematical Modeling Languages That
www.nature.com/npjsba ARTICLE OPEN Characteristics of mathematical modeling languages that facilitate model reuse in systems biology: a software engineering perspective ✉ Christopher Schölzel 1 , Valeria Blesius1, Gernot Ernst2,3 and Andreas Dominik 1 Reuse of mathematical models becomes increasingly important in systems biology as research moves toward large, multi-scale models composed of heterogeneous subcomponents. Currently, many models are not easily reusable due to inflexible or confusing code, inappropriate languages, or insufficient documentation. Best practice suggestions rarely cover such low-level design aspects. This gap could be filled by software engineering, which addresses those same issues for software reuse. We show that languages can facilitate reusability by being modular, human-readable, hybrid (i.e., supporting multiple formalisms), open, declarative, and by supporting the graphical representation of models. Modelers should not only use such a language, but be aware of the features that make it desirable and know how to apply them effectively. For this reason, we compare existing suitable languages in detail and demonstrate their benefits for a modular model of the human cardiac conduction system written in Modelica. npj Systems Biology and Applications (2021) 7:27 ; https://doi.org/10.1038/s41540-021-00182-w 1234567890():,; INTRODUCTION descriptions of experiment setup or design choices6–8. A recent As the understanding of biological systems grows, it becomes study by curators of the BioModels database showed that only 8 more and more apparent that their behavior cannot be reliably 51% of 455 published models were directly reproducible .Inan 9 predicted without the help of mathematical models. In the past, extreme case, Topalidou et al. -
Strategic Location and Dispatch Management of Assets in a Military Medical Evacuation Enterprise Phillip R
Air Force Institute of Technology AFIT Scholar Theses and Dissertations Student Graduate Works 6-19-2019 Strategic Location and Dispatch Management of Assets in a Military Medical Evacuation Enterprise Phillip R. Jenkins Follow this and additional works at: https://scholar.afit.edu/etd Part of the Operations and Supply Chain Management Commons Recommended Citation Jenkins, Phillip R., "Strategic Location and Dispatch Management of Assets in a Military Medical Evacuation Enterprise" (2019). Theses and Dissertations. 2292. https://scholar.afit.edu/etd/2292 This Dissertation is brought to you for free and open access by the Student Graduate Works at AFIT Scholar. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of AFIT Scholar. For more information, please contact [email protected]. Strategic Location and Dispatch Management of Assets in a Military Medical Evacuation Enterprise DISSERTATION Phillip R. Jenkins, Capt, USAF AFIT-ENS-DS-19-J-037 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DISTRIBUTION STATEMENT A APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. The views expressed in this document are those of the author and do not reflect the official policy or position of the United States Air Force, the United States Department of Defense or the United States Government. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. AFIT-ENS-DS-19-J-037 STRATEGIC LOCATION AND DISPATCH MANAGEMENT OF ASSETS IN A MILITARY MEDICAL EVACUATION ENTERPRISE DISSERTATION Presented to the Faculty Graduate School of Engineering and Management Air Force Institute of Technology Air University Air Education and Training Command in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Phillip R. -
A History of Clojure
A History of Clojure RICH HICKEY, Cognitect, Inc., USA Shepherd: Mira Mezini, Technische Universität Darmstadt, Germany Clojure was designed to be a general-purpose, practical functional language, suitable for use by professionals wherever its host language, e.g., Java, would be. Initially designed in 2005 and released in 2007, Clojure is a dialect of Lisp, but is not a direct descendant of any prior Lisp. It complements programming with pure functions of immutable data with concurrency-safe state management constructs that support writing correct multithreaded programs without the complexity of mutex locks. Clojure is intentionally hosted, in that it compiles to and runs on the runtime of another language, such as the JVM. This is more than an implementation strategy; numerous features ensure that programs written in Clojure can leverage and interoperate with the libraries of the host language directly and efficiently. In spite of combining two (at the time) rather unpopular ideas, functional programming and Lisp, Clojure has since seen adoption in industries as diverse as finance, climate science, retail, databases, analytics, publishing, healthcare, advertising and genomics, and by consultancies and startups worldwide, much to the career-altering surprise of its author. Most of the ideas in Clojure were not novel, but their combination puts Clojure in a unique spot in language design (functional, hosted, Lisp). This paper recounts the motivation behind the initial development of Clojure and the rationale for various design decisions and language constructs. It then covers its evolution subsequent to release and adoption. CCS Concepts: • Software and its engineering ! General programming languages; • Social and pro- fessional topics ! History of programming languages. -
Lisp and Scheme I
4/10/2012 Versions of LISP Why Study Lisp? • LISP is an acronym for LISt Processing language • It’s a simple, elegant yet powerful language • Lisp (b. 1958) is an old language with many variants • You will learn a lot about PLs from studying it – Fortran is only older language still in wide use • We’ll look at how to implement a Scheme Lisp and – Lisp is alive and well today interpreter in Scheme and Python • Most modern versions are based on Common Lisp • Scheme is one of the major variants • Many features, once unique to Lisp, are now in – We’ll use Scheme, not Lisp, in this class “mainstream” PLs: python, javascript, perl … Scheme I – Scheme is used for CS 101 in some universities • It will expand your notion of what a PL can be • The essentials haven’t changed much • Lisp is considered hip and esoteric among computer scientists LISP Features • S-expression as the universal data type – either at atom (e.g., number, symbol) or a list of atoms or sublists • Functional Programming Style – computation done by applying functions to arguments, functions are first class objects, minimal use of side-effects • Uniform Representation of Data & Code – (A B C D) can be interpreted as data (i.e., a list of four elements) or code (calling function ‘A’ to the three parameters B, C, and D) • Reliance on Recursion – iteration is provided too, but We lost the documentation on quantum mechanics. You'll have to decode recursion is considered more natural and elegant the regexes yourself. • Garbage Collection – frees programmer’s explicit memory management How Programming Language Fanboys See Each Others’ Languages 1 4/10/2012 What’s Functional Programming? Pure Lisp and Common Lisp Scheme • The FP paradigm: computation is applying • Lisp has a small and elegant conceptual core • Scheme is a dialect of Lisp that is favored by functions to data that has not changed much in almost 50 years. -
Lists in Lisp and Scheme
Lists in Lisp and Scheme • Lists are Lisp’s fundamental data structures • However, it is not the only data structure Lists in Lisp – There are arrays, characters, strings, etc. – Common Lisp has moved on from being merely a LISt Processor and Scheme • However, to understand Lisp and Scheme you must understand lists – common funcAons on them – how to build other useful data structures with them In the beginning was the cons (or pair) Pairs nil • What cons really does is combines two objects into a a two-part object called a cons in Lisp and a pair in • Lists in Lisp and Scheme are defined as Scheme • Conceptually, a cons is a pair of pointers -- the first is pairs the car, and the second is the cdr • Any non empty list can be considered as a • Conses provide a convenient representaAon for pairs pair of the first element and the rest of of any type • The two halves of a cons can point to any kind of the list object, including conses • We use one half of the cons to point to • This is the mechanism for building lists the first element of the list, and the other • (pair? ‘(1 2) ) => #t to point to the rest of the list (which is a nil either another cons or nil) 1 Box nota:on Z What sort of list is this? null Where null = ‘( ) null a a d A one element list (a) null null b c a b c > (set! z (list ‘a (list ‘b ‘c) ‘d)) (car (cdr z)) A list of 3 elements (a b c) (A (B C) D) ?? Pair? Equality • Each Ame you call cons, Scheme allocates a new memory with room for two pointers • The funcAon pair? returns true if its • If we call cons twice with the -
First-Class Dynamic Types (2019)
First-Class Dynamic Types∗ Michael Homer Timothy Jones James Noble School of Engineering Montoux School of Engineering and Computer Science New York, USA and Computer Science Victoria University of Wellington [email protected] Victoria University of Wellington New Zealand New Zealand [email protected] [email protected] Abstract 1 Introduction Since LISP, dynamic languages have supported dynamically- Most dynamically-typed languages do not provide much sup- checked type annotations. Even in dynamic languages, these port for programmers incorporating type checks in their annotations are typically static: tests are restricted to check- programs. Object-oriented languages have dynamic dispatch ing low-level features of objects and values, such as primi- and often explicit “instance of” reflective operations, grad- tive types or membership of an explicit programmer-defined ual typing provides mixed-mode enforcement of a single class. static type system, and functional languages often include We propose much more dynamic types for dynamic lan- pattern-matching partial functions, all of which are relatively guages — first-class objects that programmers can custom- limited at one end of the spectrum. At the other end, lan- ise, that can be composed with other types and depend on guages like Racket support higher-order dynamic contract computed values — and to use these first-class type-like val- systems, wrapping objects to verify contracts lazily, and with ues as types. In this way programs can define their own con- concomitant power, complexity, and overheads [10, 51]. ceptual models of types, extending both the kinds of tests Programmers may wish for a greater level of run-time programs can make via types, and the guarantees those tests checking than provided by the language, or merely different can provide. -
Multiple Dispatch As Dispatch on Tuples Gary T
Computer Science Technical Reports Computer Science 7-1998 Multiple Dispatch as Dispatch on Tuples Gary T. Leavens Iowa State University Todd Millstein Iowa State University Follow this and additional works at: http://lib.dr.iastate.edu/cs_techreports Part of the Systems Architecture Commons, and the Theory and Algorithms Commons Recommended Citation Leavens, Gary T. and Millstein, Todd, "Multiple Dispatch as Dispatch on Tuples" (1998). Computer Science Technical Reports. 131. http://lib.dr.iastate.edu/cs_techreports/131 This Article is brought to you for free and open access by the Computer Science at Iowa State University Digital Repository. It has been accepted for inclusion in Computer Science Technical Reports by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Multiple Dispatch as Dispatch on Tuples Abstract Many popular object-oriented programming languages, such as C++, Smalltalk-80, Java, and Eiffel, do not support multiple dispatch. Yet without multiple dispatch, programmers find it difficult to express binary methods and design patterns such as the ``visitor'' pattern. We describe a new, simple, and orthogonal way to add multimethods to single-dispatch object-oriented languages, without affecting existing code. The new mechanism also clarifies many differences between single and multiple dispatch. Keywords Multimethods, generic functions, object-oriented programming languages, single dispatch, multiple dispatch, tuples, product types, encapsulation, -
Array Operators Using Multiple Dispatch: a Design Methodology for Array Implementations in Dynamic Languages
Array Operators Using Multiple Dispatch: A design methodology for array implementations in dynamic languages The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Jeff Bezanson, Jiahao Chen, Stefan Karpinski, Viral Shah, and Alan Edelman. 2014. Array Operators Using Multiple Dispatch: A design methodology for array implementations in dynamic languages. In Proceedings of ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming (ARRAY '14). ACM, New York, NY, USA, 56-61, 6 pages. As Published http://dx.doi.org/10.1145/2627373.2627383 Publisher Association for Computing Machinery (ACM) Version Author's final manuscript Citable link http://hdl.handle.net/1721.1/92858 Terms of Use Creative Commons Attribution-Noncommercial-Share Alike Detailed Terms http://creativecommons.org/licenses/by-nc-sa/4.0/ Array Operators Using Multiple Dispatch Array Operators Using Multiple Dispatch A design methodology for array implementations in dynamic languages Jeff Bezanson Jiahao Chen Stefan Karpinski Viral Shah Alan Edelman MIT Computer Science and Artificial Intelligence Laboratory [email protected], [email protected], [email protected], [email protected], [email protected] Abstract ficient, such as loop fusion for array traversals and common subex- Arrays are such a rich and fundamental data type that they tend to pression elimination for indexing operations [3, 24]. Many lan- be built into a language, either in the compiler or in a large low- guage implementations therefore choose to build array semantics level library. Defining this functionality at the user level instead into compilers. provides greater flexibility for application domains not envisioned Only a few of the languages that support n-arrays, however, by the language designer.