The cognitive construction of programs by novice programmers : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University

Human memory and cognition are studied to aid novice programmers with the cognitive construction and the acquisition of program plans. Particular emphasis is placed on the storage and retrieval of program knowledge, the cognitive structure of stored program knowledge, the effects of transferring cognitive structures from one programming language to another, and the learning activities involved with learning a new programming language. Cognitive principles are applied to the design of a programming language and environment. The design of both the programming language and environment are discussed together with an introduction of how they are used. The hypothetical results of two experiments are argued to demonstrate that the programming language and environment are well suited in supporting the development of program plans

Non-linear Pattern Matching with Backtracking for Non-free Data Types

Non-free data types are data types whose data have no canonical forms. For example, multisets are non-free data types because the multiset $\{a,b,b\}$ has two other equivalent but literally different forms $\{b,a,b\}$ and $\{b,b,a\}$. Pattern matching is known to provide a handy tool set to treat such data types. Although many studies on pattern matching and implementations for practical programming languages have been proposed so far, we observe that none of these studies satisfy all the criteria of practical pattern matching, which are as follows: i) efficiency of the backtracking algorithm for non-linear patterns, ii) extensibility of matching process, and iii) polymorphism in patterns. This paper aims to design a new pattern-matching-oriented programming language that satisfies all the above three criteria. The proposed language features clean Scheme-like syntax and efficient and extensible pattern matching semantics. This programming language is especially useful for the processing of complex non-free data types that not only include multisets and sets but also graphs and symbolic mathematical expressions. We discuss the importance of our criteria of practical pattern matching and how our language design naturally arises from the criteria. The proposed language has been already implemented and open-sourced as the Egison programming language

Acute: high-level programming language design for distributed computation

Existing languages provide good support for typeful programming of standalone programs. In a distributed system, however, there may be interaction between multiple instances of many distinct programs, sharing some (but not necessarily all) of their module structure, and with some instances rebuilt with new versions of certain modules as time goes on. In this paper we discuss programming language support for such systems, focussing on their typing and naming issues. We describe an experimental language, Acute, which extends an ML core to support distributed development, deployment, and execution, allowing type-safe interaction between separately-built programs. The main features are: (1) type-safe marshalling of arbitrary values; (2) type names that are generated (freshly and by hashing) to ensure that type equality tests suffice to protect the invariants of abstract types, across the entire distributed system; (3) expression-level names generated to ensure that name equality tests suffice for type-safety of associated values, e.g. values carried on named channels; (4) controlled dynamic rebinding of marshalled values to local resources; and (5) thunkification of threads and mutexes to support computation mobility. These features are a large part of what is needed for typeful distributed programming. They are a relatively lightweight extension of ML, should be efficiently implementable, and are expressive enough to enable a wide variety of distributed infrastructure layers to be written as simple library code above the byte-string network and persistent store APIs. This disentangles the language runtime from communication intricacies. This paper highlights the main design choices in Acute. It is supported by a full language definition (of typing, compilation, and operational semantics), by a prototype implementation, and by example distribution libraries

PENCIL: Towards a Platform-Neutral Compute Intermediate Language for DSLs

We motivate the design and implementation of a platform-neutral compute intermediate language (PENCIL) for productive and performance-portable accelerator programming

From Events to Reactions: A Progress Report

Syndicate is a new coordinated, concurrent programming language. It occupies a novel point on the spectrum between the shared-everything paradigm of threads and the shared-nothing approach of actors. Syndicate actors exchange messages and share common knowledge via a carefully controlled database that clearly scopes conversations. This approach clearly simplifies coordination of concurrent activities. Experience in programming with Syndicate, however, suggests a need to raise the level of linguistic abstraction. In addition to writing event handlers and managing event subscriptions directly, the language will have to support a reactive style of programming. This paper presents event-oriented Syndicate programming and then describes a preliminary design for augmenting it with new reactive programming constructs.Comment: In Proceedings PLACES 2016, arXiv:1606.0540