Type-Safe Polyvariadic Event Correlation 3
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Why Untyped Nonground Metaprogramming Is Not (Much Of) a Problem
NORTH- HOLLAND WHY UNTYPED NONGROUND METAPROGRAMMING IS NOT (MUCH OF) A PROBLEM BERN MARTENS* and DANNY DE SCHREYE+ D We study a semantics for untyped, vanilla metaprograms, using the non- ground representation for object level variables. We introduce the notion of language independence, which generalizes range restriction. We show that the vanilla metaprogram associated with a stratified normal oljjctct program is weakly stratified. For language independent, stratified normal object programs, we prove that there is a natural one-to-one correspon- dence between atoms p(tl, . , tr) in the perfect Herbrand model of t,he object program and solve(p(tl, , tT)) atoms in the weakly perfect Her\) and model of the associated vanilla metaprogram. Thus, for this class of programs, the weakly perfect, Herbrand model provides a sensible SC mantics for the metaprogram. We show that this result generalizes to nonlanguage independent programs in the context of an extended Hcr- brand semantics, designed to closely mirror the operational behavior of logic programs. Moreover, we also consider a number of interesting exterl- sions and/or variants of the basic vanilla metainterpreter. For instance. WC demonstrate how our approach provides a sensible semantics for a limit4 form of amalgamation. a “Partly supported by the Belgian National Fund for Scientific Research, partly by ESPRlT BRA COMPULOG II, Contract 6810, and partly by GOA “Non-Standard Applications of Ab- stract Interpretation,” Belgium. TResearch Associate of the Belgian National Fund for Scientific Research Address correspondence to Bern Martens and Danny De Schreye, Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A. B-3001 Hevrrlee Belgium E-mail- {bern, dannyd}@cs.kuleuven.ac.be. -
What Is Spring Framework?
Software Engineering a.a. 2019-2020 Introduction to Spring Framework Prof. Luca Mainetti Università del Salento Roadmap ■ Introduction to Spring ■ Dependency Injection and IoC ■ Bean ■ AoP ■ Module Architecture Introduction to Spring Framework 2 Luca Mainetti What Is Spring Framework? ■ Spring is the most popular application development framework for Java enterprise ■ Open source Java platform since 2003. ■ Spring supports all main application servers and JEE standards ■ Spring handles the infrastructure so you can focus on your application ■ Current version: 5.0.X Introduction to Spring Framework 3 Luca Mainetti What does Spring offer? ■ Dependency Injection – Also known as IoC (Inversion of Control) ■ Aspect Oriented Programming – Runtime injection-based ■ Portable Service Abstractions – The rest of spring • ORM, DAO, Web MVC, Web, etc. • Allows access to these without knowing how they actually work Introduction to Spring Framework 4 Luca Mainetti Dependency Injection ■ The technology that actually defines Spring (Heart of Spring). ■ Dependency Injection helps us to keep our classes as indepedent as possible. – Increase reuse by applying low coupling – Easy testing – More understandable An injection is the passing of a dependency (a service) to a dependent object (a client). Passing the service to the client, rather than allowing a client to build or find the service, is the fundamental requirement of the pattern. Introduction to Spring Framework 5 Luca Mainetti Dependency Injection and Inversion of Control (IoC) In software engineering, inversion of control (IoC) describes a design in which custom-written portions of a computer program receive the flow of control from a generic, reusable library. ■ The Inversion of Control (IoC) is a general concept, and it can be expressed in many different ways and dependency Injection is merely one concrete example of Inversion of Control. -
Ioc Containers in Spring
301AA - Advanced Programming Lecturer: Andrea Corradini [email protected] http://pages.di.unipi.it/corradini/ AP-2018-11: Frameworks and Inversion of Control Frameworks and Inversion of Control • Recap: JavaBeans as Components • Frameworks, Component Frameworks and their features • Frameworks vs IDEs • Inversion of Control and Containers • Frameworks vs Libraries • Decoupling Components • Dependency Injection • IoC Containers in Spring 2 Components: a recap A software component is a unit of composition with contractually specified interfaces and explicit context dependencies only. A software component can be deployed independently and is subject to composition by third party. Clemens Szyperski, ECOOP 1996 • Examples: Java Beans, CLR Assemblies • Contractually specified interfaces: events, methods and properties • Explicit context dependencies: serializable, constructor with no argument • Subject to composition: connection to other beans – Using connection oriented programming (event source and listeners/delegates) 3 Towards Component Frameworks • Software Framework: A collection of common code providing generic functionality that can be selectively overridden or specialized by user code providing specific functionality • Application Framework: A software framework used to implement the standard structure of an application for a specific development environment. • Examples: – GUI Frameworks – Web Frameworks – Concurrency Frameworks 4 Examples of Frameworks Web Application Frameworks GUI Toolkits 5 Examples: General Software Frameworks – .NET – Windows platform. Provides language interoperability – Android SDK – Supports development of apps in Java (but does not use a JVM!) – Cocoa – Apple’s native OO API for macOS. Includes C standard library and the Objective-C runtime. – Eclipse – Cross-platform, easily extensible IDE with plugins 6 Examples: GUI Frameworks • Frameworks for Application with GUI – MFC - Microsoft Foundation Class Library. -
Practical Reflection and Metaprogramming for Dependent
Practical Reflection and Metaprogramming for Dependent Types David Raymond Christiansen Advisor: Peter Sestoft Submitted: November 2, 2015 i Abstract Embedded domain-specific languages are special-purpose pro- gramming languages that are implemented within existing general- purpose programming languages. Dependent type systems allow strong invariants to be encoded in representations of domain-specific languages, but it can also make it difficult to program in these em- bedded languages. Interpreters and compilers must always take these invariants into account at each stage, and authors of embedded languages must work hard to relieve users of the burden of proving these properties. Idris is a dependently typed functional programming language whose semantics are given by elaboration to a core dependent type theory through a tactic language. This dissertation introduces elabo- rator reflection, in which the core operators of the elaborator are real- ized as a type of computations that are executed during the elab- oration process of Idris itself, along with a rich API for reflection. Elaborator reflection allows domain-specific languages to be imple- mented using the same elaboration technology as Idris itself, and it gives them additional means of interacting with native Idris code. It also allows Idris to be used as its own metalanguage, making it into a programmable programming language and allowing code re-use across all three stages: elaboration, type checking, and execution. Beyond elaborator reflection, other forms of compile-time reflec- tion have proven useful for embedded languages. This dissertation also describes error reflection, in which Idris code can rewrite DSL er- ror messages before presenting domain-specific messages to users, as well as a means for integrating quasiquotation into a tactic-based elaborator so that high-level syntax can be used for low-level reflected terms. -
Reversible Programming with Negative and Fractional Types
9 A Computational Interpretation of Compact Closed Categories: Reversible Programming with Negative and Fractional Types CHAO-HONG CHEN, Indiana University, USA AMR SABRY, Indiana University, USA Compact closed categories include objects representing higher-order functions and are well-established as models of linear logic, concurrency, and quantum computing. We show that it is possible to construct such compact closed categories for conventional sum and product types by defining a dual to sum types, a negative type, and a dual to product types, a fractional type. Inspired by the categorical semantics, we define a sound operational semantics for negative and fractional types in which a negative type represents a computational effect that “reverses execution flow” and a fractional type represents a computational effect that“garbage collects” particular values or throws exceptions. Specifically, we extend a first-order reversible language of type isomorphisms with negative and fractional types, specify an operational semantics for each extension, and prove that each extension forms a compact closed category. We furthermore show that both operational semantics can be merged using the standard combination of backtracking and exceptions resulting in a smooth interoperability of negative and fractional types. We illustrate the expressiveness of this combination by writing a reversible SAT solver that uses back- tracking search along freshly allocated and de-allocated locations. The operational semantics, most of its meta-theoretic properties, and all examples are formalized in a supplementary Agda package. CCS Concepts: • Theory of computation → Type theory; Abstract machines; Operational semantics. Additional Key Words and Phrases: Abstract Machines, Duality of Computation, Higher-Order Reversible Programming, Termination Proofs, Type Isomorphisms ACM Reference Format: Chao-Hong Chen and Amr Sabry. -
Let's Get Functional
5 LET’S GET FUNCTIONAL I’ve mentioned several times that F# is a functional language, but as you’ve learned from previous chapters you can build rich applications in F# without using any functional techniques. Does that mean that F# isn’t really a functional language? No. F# is a general-purpose, multi paradigm language that allows you to program in the style most suited to your task. It is considered a functional-first lan- guage, meaning that its constructs encourage a functional style. In other words, when developing in F# you should favor functional approaches whenever possible and switch to other styles as appropriate. In this chapter, we’ll see what functional programming really is and how functions in F# differ from those in other languages. Once we’ve estab- lished that foundation, we’ll explore several data types commonly used with functional programming and take a brief side trip into lazy evaluation. The Book of F# © 2014 by Dave Fancher What Is Functional Programming? Functional programming takes a fundamentally different approach toward developing software than object-oriented programming. While object-oriented programming is primarily concerned with managing an ever-changing system state, functional programming emphasizes immutability and the application of deterministic functions. This difference drastically changes the way you build software, because in object-oriented programming you’re mostly concerned with defining classes (or structs), whereas in functional programming your focus is on defining functions with particular emphasis on their input and output. F# is an impure functional language where data is immutable by default, though you can still define mutable data or cause other side effects in your functions. -
Inversion of Control in Spring – Using Annotation
Inversion of Control in Spring – Using Annotation In this chapter, we will configure Spring beans and the Dependency Injection using annotations. Spring provides support for annotation-based container configuration. We will go through bean management using stereotypical annotations and bean scope using annotations. We will then take a look at an annotation called @Required, which allows us to specify which dependencies are actually required. We will also see annotation-based dependency injections and life cycle annotations. We will use the autowired annotation to wire up dependencies in the same way as we did using XML in the previous chapter. You will then learn how to add dependencies by type and by name. We will also use qualifier to narrow down Dependency Injections. We will also understand how to perform Java-based configuration in Spring. We will then try to listen to and publish events in Spring. We will also see how to reference beans using Spring Expression Language (SpEL), invoke methods using SpEL, and use operators with SpEL. We will then discuss regular expressions using SpEL. Spring provides text message and internationalization, which we will learn to implement in our application. Here's a list of the topics covered in this chapter: • Container configuration using annotations • Java-based configuration in Spring • Event handling in Spring • Text message and internationalization [ 1 ] Inversion of Control in Spring – Using Annotation Container configuration using annotation Container configuration using Spring XML sometimes raises the possibility of delays in application development and maintenance due to size and complexity. To solve this issue, the Spring Framework supports container configuration using annotations without the need of a separate XML definition. -
Notes on Functional Programming with Haskell
Notes on Functional Programming with Haskell H. Conrad Cunningham [email protected] Multiparadigm Software Architecture Group Department of Computer and Information Science University of Mississippi 201 Weir Hall University, Mississippi 38677 USA Fall Semester 2014 Copyright c 1994, 1995, 1997, 2003, 2007, 2010, 2014 by H. Conrad Cunningham Permission to copy and use this document for educational or research purposes of a non-commercial nature is hereby granted provided that this copyright notice is retained on all copies. All other rights are reserved by the author. H. Conrad Cunningham, D.Sc. Professor and Chair Department of Computer and Information Science University of Mississippi 201 Weir Hall University, Mississippi 38677 USA [email protected] PREFACE TO 1995 EDITION I wrote this set of lecture notes for use in the course Functional Programming (CSCI 555) that I teach in the Department of Computer and Information Science at the Uni- versity of Mississippi. The course is open to advanced undergraduates and beginning graduate students. The first version of these notes were written as a part of my preparation for the fall semester 1993 offering of the course. This version reflects some restructuring and revision done for the fall 1994 offering of the course|or after completion of the class. For these classes, I used the following resources: Textbook { Richard Bird and Philip Wadler. Introduction to Functional Program- ming, Prentice Hall International, 1988 [2]. These notes more or less cover the material from chapters 1 through 6 plus selected material from chapters 7 through 9. Software { Gofer interpreter version 2.30 (2.28 in 1993) written by Mark P. -
Monadic Functional Reactive Programming
Monadic Functional Reactive Programming Atze van der Ploeg Centrum Wiskunde & Informatica [email protected] Abstract FRP is based on the notion of a reactive computation: a monadic Functional Reactive Programming (FRP) is a way to program reac- computation which may require the occurrence of external events tive systems in functional style, eliminating many of the problems to continue. The Monadic FRP variant of a signal is a signal that arise from imperative techniques. In this paper, we present an computation: a reactive computation that may also emit values alternative FRP formulation that is based on the notion of a reac- during the computation. tive computation: a monadic computation which may require the This novel formulation has two differences with other FRP occurrence of external events to continue. A signal computation approaches: is a reactive computation that may also emit values. In contrast to • In contrast to signals in other FRP formulations, signal compu- signals in other FRP formulations, signal computations can end, tations can end. This leads to a simple, monadic interface for leading to a monadic interface for sequencing behavioral changes. sequencing behavioral changes. This interface has several advantages: routing is implicit, sequencing • behaviors is easier and more intuitive than the switching combina- In other FRP approaches, either the entire FRP expression is tors found in other FRP approaches, and dynamic lists require much re-evaluated on each external stimulus, or impure techniques less boilerplate code. In other FRP approaches, either the entire are used to prevent redundant re-computations: re-computing FRP expression is re-evaluated on each external stimulus, or impure the current value of signal while the input it depends on has not techniques are used to prevent redundant re-computations. -
Design Patterns in Ocaml
Design Patterns in OCaml Antonio Vicente [email protected] Earl Wagner [email protected] Abstract The GOF Design Patterns book is an important piece of any professional programmer's library. These patterns are generally considered to be an indication of good design and development practices. By giving an implementation of these patterns in OCaml we expected to better understand the importance of OCaml's advanced language features and provide other developers with an implementation of these familiar concepts in order to reduce the effort required to learn this language. As in the case of Smalltalk and Scheme+GLOS, OCaml's higher order features allows for simple elegant implementation of some of the patterns while others were much harder due to the OCaml's restrictive type system. 1 Contents 1 Background and Motivation 3 2 Results and Evaluation 3 3 Lessons Learned and Conclusions 4 4 Creational Patterns 5 4.1 Abstract Factory . 5 4.2 Builder . 6 4.3 Factory Method . 6 4.4 Prototype . 7 4.5 Singleton . 8 5 Structural Patterns 8 5.1 Adapter . 8 5.2 Bridge . 8 5.3 Composite . 8 5.4 Decorator . 9 5.5 Facade . 10 5.6 Flyweight . 10 5.7 Proxy . 10 6 Behavior Patterns 11 6.1 Chain of Responsibility . 11 6.2 Command . 12 6.3 Interpreter . 13 6.4 Iterator . 13 6.5 Mediator . 13 6.6 Memento . 13 6.7 Observer . 13 6.8 State . 14 6.9 Strategy . 15 6.10 Template Method . 15 6.11 Visitor . 15 7 References 18 2 1 Background and Motivation Throughout this course we have seen many examples of methodologies and tools that can be used to reduce the burden of working in a software project. -
Scala by Example (2009)
Scala By Example DRAFT January 13, 2009 Martin Odersky PROGRAMMING METHODS LABORATORY EPFL SWITZERLAND Contents 1 Introduction1 2 A First Example3 3 Programming with Actors and Messages7 4 Expressions and Simple Functions 11 4.1 Expressions And Simple Functions...................... 11 4.2 Parameters.................................... 12 4.3 Conditional Expressions............................ 15 4.4 Example: Square Roots by Newton’s Method................ 15 4.5 Nested Functions................................ 16 4.6 Tail Recursion.................................. 18 5 First-Class Functions 21 5.1 Anonymous Functions............................. 22 5.2 Currying..................................... 23 5.3 Example: Finding Fixed Points of Functions................ 25 5.4 Summary..................................... 28 5.5 Language Elements Seen So Far....................... 28 6 Classes and Objects 31 7 Case Classes and Pattern Matching 43 7.1 Case Classes and Case Objects........................ 46 7.2 Pattern Matching................................ 47 8 Generic Types and Methods 51 8.1 Type Parameter Bounds............................ 53 8.2 Variance Annotations.............................. 56 iv CONTENTS 8.3 Lower Bounds.................................. 58 8.4 Least Types.................................... 58 8.5 Tuples....................................... 60 8.6 Functions.................................... 61 9 Lists 63 9.1 Using Lists.................................... 63 9.2 Definition of class List I: First Order Methods.............. -
Metaprogramming with Julia
Metaprogramming with Julia https://szufel.pl Programmers effort vs execution speed Octave R Python Matlab time, time, log scale - C JavaScript Java Go Julia C rozmiar kodu Sourcewego w KB Source: http://www.oceanographerschoice.com/2016/03/the-julia-language-is-the-way-of-the-future/ 2 Metaprogramming „Metaprogramming is a programming technique in which computer programs have the ability to treat other programs as their data. It means that a program can be designed to read, generate, analyze or transform other programs, and even modify itself while running.” (source: Wikipedia) julia> code = Meta.parse("x=5") :(x = 5) julia> dump(code) Expr head: Symbol = args: Array{Any}((2,)) 1: Symbol x 2: Int64 5 3 Metaprogramming (cont.) julia> code = Meta.parse("x=5") :(x = 5) julia> dump(code) Expr head: Symbol = args: Array{Any}((2,)) 1: Symbol x 2: Int64 5 julia> eval(code) 5 julia> x 5 4 Julia Compiler system not quite accurate picture... Source: https://www.researchgate.net/ publication/301876510_High- 5 level_GPU_programming_in_Julia Example 1. Select a field from an object function getValueOfA(x) return x.a end function getValueOf(x, name::String) return getproperty(x, Symbol(name)) end function getValueOf2(name::String) field = Symbol(name) code = quote (obj) -> obj.$field end return eval(code) end function getValueOf3(name::String) return eval(Meta.parse("obj -> obj.$name")) end 6 Let’s test using BenchmarkTools struct MyStruct a b end x = MyStruct(5,6) @btime getValueOfA($x) @btime getValueOf($x,"a") const getVal2 = getValueOf2("a") @btime