This paper presents the design and implementation of a sequential simulator for the parallel functional language BSML based on the parallel computation model Bulk Synchronous Parallelism (BSP). This simulator is imple...
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ISBN:
(纸本)9781538693803
This paper presents the design and implementation of a sequential simulator for the parallel functional language BSML based on the parallel computation model Bulk Synchronous Parallelism (BSP). This simulator is implemented in sequential, runs in any browser, and provides a graphical representation of the parallel executions. Due to the pure functional nature of BSML, the results obtained by this simulator are the same than the results that could be obtained by executing the program in parallel.
If your application source code is overly verbose, it can be a nightmare to maintain. Write concise and expressive, type-safe code in an environment that lets you build for the JVM, browser, and more.Key Features• Exp...
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ISBN:
(数字)9781789534702
ISBN:
(纸本)9781789533835
If your application source code is overly verbose, it can be a nightmare to maintain. Write concise and expressive, type-safe code in an environment that lets you build for the JVM, browser, and more.
Key Features
• Expert guidance that shows you to efficiently use both object-oriented and functional programming techniques
• Understand functional programming libraries, such as Cats and Scalaz, and use them to augment your Scala development
• Perfectly balances theory and hands-on exercises, assessments, and activities
Book Description
This book teaches you how to build and contribute to Scala programs, recognizing common patterns and techniques used with the language. You’ll learn how to write concise, functional code with Scala. After an introduction to core concepts, syntax, and writing example applications with scalac, you’ll learn about the Scala Collections API and how the language handles type safety via static types out-of-the-box. You’ll then learn about advanced functional programming patterns, and how you can write your own Domain Specific Languages (DSLs). By the end of the book, you’ll be equipped with the skills you need to successfully build smart, efficient applications in Scala that can be compiled to the JVM.
What you will learn
• Understand the key language syntax and core concepts for application development
• Master the type system to create scalable type-safe applications while cutting down your time spent debugging
• Understand how you can work with advanced data structures via built-in features such as the Collections library
• Use classes, objects, and traits to transform a trivial chatbot program into a useful assistant
• Understand what are pure functions, immutability, and higher-order functions
• Recognize and implement popular functional programming design patterns
Who this book is for
This is an ideal book for developers who are looking to learn Scala, and is particularly well suited for Java developers looking to migrate across
How to integrate mathematical thinking more fully into the computer science curriculum is a perennial problem for CS educators. A key part of that integration is designing the discrete math course so that its relevanc...
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Reproducing Kernel Hilbert Space (RKHS)-based methods are widely used in signal processing and machine learning applications. Yet, they suffer from a parameter selection issue: selecting the RKHS in which to operate (...
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The paper deals with the fundamental computational rule of functional programming languages, namely the rule of beta conversion. This rule specifies the way in which a function f is applied to its argument a. There ar...
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This paper presents how functional programming (FP) helps to provide an other formal semantics (relation between the syntax and the model of computation) for Business Process Modeling (BPM);a semantics relatively diff...
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This paper presents how functional programming (FP) helps to provide an other formal semantics (relation between the syntax and the model of computation) for Business Process Modeling (BPM);a semantics relatively different from Object Oriented semantics. More precisely, it proposes a general methodology to model business processes using mathematical functions and higher-order functions. We describe the basic part of Business Process Modeling, behavioral semantics via Petri Nets (PN) and functional implementation of the models. Also, we will see how the business process model is translated into its equivalent form in Petri Nets and how these can be described through functional programming. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
This paper presents how functional programming (FP) helps to provide an other formal semantics (relation between the syntax and the model of computation) for Business Process Modeling (BPM); a semantics relatively dif...
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This paper presents a theoretical foundation for functional language implementations of Behaviour -Interaction -Priority (BIP). We introduce a set of connector combinators describing synchronisation, data transfer, pr...
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This paper presents a theoretical foundation for functional language implementations of Behaviour -Interaction -Priority (BIP). We introduce a set of connector combinators describing synchronisation, data transfer, priorities and dynamicity in a principled way. A static type system ensures the soundness of connector semantics. Based on this foundation, we implemented BIP as an embedded domain specific language (DSL) in Haskell and Scala. The DSL embedding allows programmers to benefit from the full expressive power of high-level languages. The clear separation of behaviour and coordination inherited from BIP leads to systems that are arguably simpler to maintain and reason about, compared to other approaches. (C) 2017 Elsevier Inc. All rights reserved.
The Lisp programming language is often described as the first functional programming language and also as an important early AI language. In the history of functional programming, however, it occupies a rather anomalo...
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The Lisp programming language is often described as the first functional programming language and also as an important early AI language. In the history of functional programming, however, it occupies a rather anomalous position, as the circumstances of its development do not fit well with the widely accepted view that functional languages have been developed through a theoretically-inspired project of deriving practical programming languages from the lambda calculus. This paper examines the origins of Lisp in the early AI programming work of the mid-to-late 1950s, and in particular in the work of Allen Newell, Cliff Shaw and Herbert Simon. Their 1956 program, the Logic Theory Machine, introduced new ideas about data and program structures that were articulated in response to perceived limitations in existing programming technique. Later writers, notably John Backus, have described these features as constituting a "programming language style" distinct from the traditional style that preceded it. The paper examines the origins of the earlier style in practices of manual computation, analyses the key technical differences between it and the style first manifested in the Logic Theory Machine, and concludes that programming practice and experience play a large and underappreciated role in the development of programming styles and languages.
functional languages offer a high level of abstraction, which results in programs that are elegant and easy to understand. Central to the development of functional programming are inductive and coinductive types and a...
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functional languages offer a high level of abstraction, which results in programs that are elegant and easy to understand. Central to the development of functional programming are inductive and coinductive types and associated programming constructs, such as pattern-matching. Whereas inductive types have a long tradition and are well supported in most languages, coinductive types are subject of more recent research and are less mainstream. We present CoCaml, a functional programming language extending OCaml, which allows us to define recursive functions on regular coinductive datatypes. These functions are defined like usual recursive functions, but parameterized by an equation solver. We present a full implementation of all the constructs and solvers and show how these can be used in a variety of examples, including operations on infinite lists, infinitary lambda-terms, and p-adic numbers.
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