Introduction To Functional Programming Prentice Hall International Series In Computing Science

We study a series of milestones leading to the emergence of lazy, higher order, polymorphically typed, purely functional programming languages. An invited lecture given at TFP12, St Andrews University, 12 June 2012.

A Computer Science introduction course ought to focus on exciting students about the subject matter and on problem solving through the methodical design of programs. An effective way to achieve both is through the development of functional video games. As most students are interested in video games, their development adds an exciting domain to any introduction to programming. This article advocates that an exciting crowning achievement for students in such a course is the design and implementation of a multiplayer distributed video game. By exploiting a domain that is popular with students, they are taught about design principles, communication protocols, and pitfalls in distributed programming. This article puts forth a successfully used design recipe that places distributed programming well within the reach of beginning students and outlines the use of this design recipe in the classroom. For those teaching beginners, this article presents a model for developing their own distributed programming module. The success of the presented methodology is measured through student feedback on their distributed programming experience. The empirical results suggest that the design and implementation of distributed functional video games is effective and well-received by students. Furthermore, the data suggests that the presented methodology fails to exhibit the gender gap common in Computer Science and is effective regardless of the programming experience CS1 students bring to the classroom.

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Paul Downen is an assistant professor at the University of Massachusetts Lowell, joining the Miner School of Computer & Information Sciences in 2021. He received a Ph.D. from the University of Oregon's Computer and Information Science Department, and has been a visiting researcher at INRIA and Microsoft Research. His research centers on using logic to improve the efficiency, correctness, and safety of programs and their compilation. Paul's thesis - for which he was awarded the University's Doctoral Research Fellowship - explored applications of proof theory towards the design and implementation of programming languages, and for verifying programs. Applications of his work have been implemented in the Glasgow Haskell Compiler, where it is being used to improve the optimization of real-world functional programs. His research appears in top conferences and journals for programming languages, such as the Journal of Functional Programming, Logical Methods in Computer Science, Fundamenta Informaticae, PLDI, ICFP, and ESOP, and has received best paper awards. These articles include a series of tutorials focused on disseminating theoretical material to a wider community, which prompted the Journal of Functional Programming to create a category of similar "tutorial" articles inspired by Paul's work. In addition to organizing the Oregon Programming Languages Summer School for several years, Paul has been instrumental in its outreach to a more diverse audience - including young students and professionals from industry - by introducing a "Foundations" lecture series accompanying OPLSS.

As shown above, the distinction between software and hardware is not asharp one. A different ontological approach to computational systemsrelies on the role of abstraction. Abstraction is a crucial element incomputer science, and it takes many different forms. Goguen &Burstall (1985) describe some of this variety, of which the followingexamples are instances. Code can be repeated during programming, bynaming text and a parameter, a practice known as proceduralabstraction. This operation has its formal basis in the abstractionoperation of the lambda calculus (see the entry on the lambda calculus) and it allows a formal mechanism known as polymorphism (Hankin 2004).Another example is typing, typical of functional programming, whichprovides an expressive system of representation for the syntacticconstructors of the language. Or else, in object-oriented design,patterns (Gamma et al. 1994) are abstracted from the common structuresthat are found in software systems and used as interfaces between theimplementation of an object and its specification.

Programs can be understood as technical artifacts because programminglanguages are defined, as any other artifact, on the basis of bothfunctional and structural properties (Turner 2014, 2018 ch. 5).Functional properties of (high level) programming languages areprovided by the semantics associated with each syntactic construct ofthe language. Turner (2014) points out that programming languages canindeed be understood as axiomatic theories only when their functionallevel is isolated. Structural properties, on the other hand, arespecified in terms of the implementation of the language, but notidentified with physical components of computing machines: given asyntactic construct of the language with an associated functionaldescription, its structural property is determined by the physicaloperations that a machine performs to implement an instruction for theconstruct at hand. For instance, the assignment construct \(x := E\)is to be linked to the physical computation of the value of expression\(E\) and to the placement of the value of \(E\) in the physicallocation \(x\). be457b7860