Thesis (Ph. D.)--College of Computing, Georgia Institute of Technology, 2005. Directed by Yannis Smaragdakis. / Spencer Rugaber, Committee Member ; Olin Shivers, Committee Member ; Mary Jean Harrold, Committee Member ; Yannis Smaragdakis, Committee Chair ; Philip Wadler, Committee Member. Includes bibliographical references.

Thesis (M. Sc.)--University of Canterbury, 2006. / Typescript (photocopy). Includes bibliographical references (leaves 101-107). Also available via the World Wide Web.

o objetivo deste trabalho é apresentar a implementação em Java de uma máquina abstrata para execução distribuída de programas funcionais. Mostra-se como as facilidades da linguagem Java foram utilizadas para a implementação de uma linguagem funcional paralela que roda os programas funcionais de forma distribuída em uma rede de computadores. Linguagens Funcionais geralmente são implementadas usando uma máquina abstrata para a execução dos programas. Essas máquinas são usualmente máquinas de redução de grafos. Para se rodar os programas funcionais na máquina virtual Java implementou-se a máquina de redução de grafos G-Machine em Java. Nesta dissertação, apresenta-se inicialmente a implementação da G-Machine em Java, realizada como primeira etapa do trabalho e discute-se a abordagem utilizada para essa implementação. Mostra-se em seguida, como os programas funcionais podem ser compilados para rodar nessa G-Machine. Na segunda etapa do trabalho, modifica-se o sistema implementado para permitir a execução distribuída dos programas funcionais. Finalmente apresenta-se uma avaliação de desempenho e mostra-se possíveis trabalhos futuros. / The objective of this work is to present the implementation in the Java language of an abstract machine for distributed execution of functional programs. We show how the Java facilities were used to implement a parallel functional programming language with a distributed runtime system. Functional Languages are usually implemented using an abstract machine to execute programs. These abstract machines are usually graph reduction machines. To mn the functional programs on the Java Virtual Machine we have implemented the G-Machine graph reduction machine in Java. In this text, we first present the implementation of the G-Machine in J ava, and discuss its implementation. Then we show how this implementation was modified to allow distributed execution of functional programs. Finally some benchmarks, possible future works and conclusions are presented.

o objetivo deste trabalho é apresentar a implementação em Java de uma máquina abstrata para execução distribuída de programas funcionais. Mostra-se como as facilidades da linguagem Java foram utilizadas para a implementação de uma linguagem funcional paralela que roda os programas funcionais de forma distribuída em uma rede de computadores. Linguagens Funcionais geralmente são implementadas usando uma máquina abstrata para a execução dos programas. Essas máquinas são usualmente máquinas de redução de grafos. Para se rodar os programas funcionais na máquina virtual Java implementou-se a máquina de redução de grafos G-Machine em Java. Nesta dissertação, apresenta-se inicialmente a implementação da G-Machine em Java, realizada como primeira etapa do trabalho e discute-se a abordagem utilizada para essa implementação. Mostra-se em seguida, como os programas funcionais podem ser compilados para rodar nessa G-Machine. Na segunda etapa do trabalho, modifica-se o sistema implementado para permitir a execução distribuída dos programas funcionais. Finalmente apresenta-se uma avaliação de desempenho e mostra-se possíveis trabalhos futuros. / The objective of this work is to present the implementation in the Java language of an abstract machine for distributed execution of functional programs. We show how the Java facilities were used to implement a parallel functional programming language with a distributed runtime system. Functional Languages are usually implemented using an abstract machine to execute programs. These abstract machines are usually graph reduction machines. To mn the functional programs on the Java Virtual Machine we have implemented the G-Machine graph reduction machine in Java. In this text, we first present the implementation of the G-Machine in J ava, and discuss its implementation. Then we show how this implementation was modified to allow distributed execution of functional programs. Finally some benchmarks, possible future works and conclusions are presented.

o objetivo deste trabalho é apresentar a implementação em Java de uma máquina abstrata para execução distribuída de programas funcionais. Mostra-se como as facilidades da linguagem Java foram utilizadas para a implementação de uma linguagem funcional paralela que roda os programas funcionais de forma distribuída em uma rede de computadores. Linguagens Funcionais geralmente são implementadas usando uma máquina abstrata para a execução dos programas. Essas máquinas são usualmente máquinas de redução de grafos. Para se rodar os programas funcionais na máquina virtual Java implementou-se a máquina de redução de grafos G-Machine em Java. Nesta dissertação, apresenta-se inicialmente a implementação da G-Machine em Java, realizada como primeira etapa do trabalho e discute-se a abordagem utilizada para essa implementação. Mostra-se em seguida, como os programas funcionais podem ser compilados para rodar nessa G-Machine. Na segunda etapa do trabalho, modifica-se o sistema implementado para permitir a execução distribuída dos programas funcionais. Finalmente apresenta-se uma avaliação de desempenho e mostra-se possíveis trabalhos futuros. / The objective of this work is to present the implementation in the Java language of an abstract machine for distributed execution of functional programs. We show how the Java facilities were used to implement a parallel functional programming language with a distributed runtime system. Functional Languages are usually implemented using an abstract machine to execute programs. These abstract machines are usually graph reduction machines. To mn the functional programs on the Java Virtual Machine we have implemented the G-Machine graph reduction machine in Java. In this text, we first present the implementation of the G-Machine in J ava, and discuss its implementation. Then we show how this implementation was modified to allow distributed execution of functional programs. Finally some benchmarks, possible future works and conclusions are presented.

Formal methods play a significant and increasing role in hardware verification, but their effectiveness can be impaired by the ac hoc nature of mainstream hardware languages such as VHDL, Verilog and SystemC, which have convoluted semantics that often necessitate contrived proof techniques. This dissertation investigates the application of formal reasoning to hardware architectures expressed in an alternative class of semantically elegant languages, which support efficient design, whilst also having been developed with proof techniques in mind. A network-on-chip architecture belonging to the SpiNNaker many-core processor is specified in Concurrent Haskell, and a hand proof is presented which verifies a novel routing mechanism by mathematical induction. A subset of Bluespec SystemVerilog (BSV) is embedded in the higher order logic of the PVS theorem prover. Owing to the clean semantics of BSV, application of monadic techniques leads to a surprisingly elegant embedding, in which hardware designs are translated into logic almost verbatim, preserving types and language constructs. Proof strategies are written in the PVS strategy language; these automatically verify temporal logic theorems concerning the resulting monadic expressions, by employing a combination of model checking and deductive reasoning. The subset of BSV which is embedded includes module definition and instantiation, methods, implicit conditions, scheduling attributes, and rule composition using methods from instantiated modules. The aforementioned subset of BSV is also embedded in the specification language of the SAL model checker, and a verification strategy is presented which combines the specialised model checking capabilities of SAL with the diverse proof strategies of PVS.

PrologPF is a parallelising compiler targeting a distributed system of general purpose workstations connected by a relatively low performance network. The source language extends standard Prolog with the integration of higher-order functions. The execution of a compiled PrologPF program proceeds in a similar manner to standard Prolog, but uses oracles in one of two modes. An oracle represents the sequence of clauses used to reach a given point in the problem search tree, and the same PrologPF executable can be used to build oracles, or follow oracles previously generated. The parallelisation strategy used by PrologPF proceeds in two phases, which this research shows can be interleaved. An initial phase searches the problem tree to a limited depth, recording the discovered incomplete paths. In the second phase these paths are allocated to the available processors in the network. Each processor follows its assigned paths and fully searches the referenced subtree, sending solutions back to a control processor. This research investigates the use of the technique with a one-time partitioning of the problem and no further scheduling communication, and with the recursive application of the partitioning technique to effect dynamic work reassignment. For a problem requiring all solutions to be found, execution completes when all the distributed processors have completed the search of their assigned subtrees. If one solution is required, the execution of all the path processors is terminated when the control processor receives the first solution. The presence of the extra-logical Prolog predicate cut in the user program conflicts with the use of oracles to represent valid open subtrees. PrologPF promotes the use of higher-order functional programming as an alternative to the use of cut. The combined language shows that functional support can be added as a consistent extension to standard Prolog.

There are multiple programming paradigms that have their own set rules forhow code should be written. Programming languages utilize one or multiple ofthese paradigms. In this thesis, we will compare object-oriented programming,that is the most used today with languages such as C++ and Java, and functionalprogramming. Functional programming was introduced in the 1950's butsuered from performance issues, and has not been used much except for in theacademic world. However, for its ability to handle concurrency and big data,functional programming is of interest in the industry again with languages suchas Scala. In functional programming side effects, any interaction outside of thefunction, are avoided as well as changing and saving state. To compare these paradigms we have chosen four dierent algorithms, whichboth of us have implemented twice, once according to object-oriented programmingand once according to functional programming. All algorithms were implementedJavaScript. JavaScript is a multiparadigm language that supportsboth functional and object-oriented programming. For all implementations,we have measured development time, lines of code, execution time and memoryusage. Our results show that object-oriented programming gave us betterperformance, but functional programming resulted in less code and a shorterdevelopment time.

Studies assessing novice programming proficiency have often found that many students coming out of introductory-level programming courses still struggle with programming. To address this, some researchers have attempted to find and develop ways to better help students succeed in learning to program. This dissertation research contributes to this area by studying the programming processes of students trained through a specific program design curriculum, How to Design Programs (HTDP). HTDP is an introductory-level curriculum for teaching program design that teaches a unique systematic process called the design recipe that leverages the structure of input data to design programs. The design recipe explicitly scaffolds learners through the program design process by asking students to produce intermediate artifacts that represent a given problem in different ways up to a program solution to the problem. Although HTDP is used in several higher-education institutions and some K-12 programs, how HTDP-trained students design programs towards problems, particularly ones with multiple task-components, has not been thoroughly studied. The overarching goal of this dissertation is to gain an understanding and insight into how students use the techniques put forth by the design recipe towards designing solutions for programming problems. I conducted a series of exploratory user studies with HTDP-trained student cohorts from HTDP course instances across two different universities to collect and analyze students’ programming process data in situ. I synthesized findings from each study towards an overall conceptual framework, which serves as a data-grounded theory that captures several facets of HTDP-trained students’ program design process. The main contribution of this work is this theory, which describes: (1) the program design-related skills that students used and the levels of complexity at which they applied these skills, (2) how students’ use of design skills evolve during a course, (3) the interactions between program design skills and course contexts that influenced how students applied their skills, and (4) the programming process patterns by which students approached the programming problems we gave and how these approaches relate towards students’ success with the problems. Using insights from the theory, I describe recommendations toward pedagogical practices for teaching HTDP-based courses, as well as broader reflections towards teaching introductory CS.

The main goal of this thesis was to implement a functional programming (FP) library named Funk that extends C# with support for concepts present in functional programming languages, such as F# and Scala. Funk utilizes many functional programming concepts, including immutability, pattern matching, and various types of monads, together with stronger typing. Introduction of these concepts into C# helps in avoiding many runtime errors and boilerplate code, and it also lets developers write C# code in a declarative rather than in an imperative way, making the day-to-day software development easier and less error-prone. Additionally, the thesis analyzes and compares Funk with existing functional programming libraries such as Language-ext and FuncSharp. Finally, it analyzes the new features of C# 8, which include nullable reference types and pattern matching and compares them with the functionalities of the Funk library.