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Designing Flexible, Modular Linguistic Abstractions

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Abstract

Programming-language design is more active than ever: existing languages are evolving continually and rapidly, and new languages keep springing up. While this constant iteration of language design aims to help programmers manage a growing software complexity, programmers are still frequently frustrated by poor design decisions in even the most essential aspects of modern programming languages. Less than satisfactory solutions to generic programming and exception handling typify this situation: the inadequacy of current solutions has even forced language designers to abandon these problematic language features. This is an unfortunate state of affairs. Language design does not have to be about abandoning old features or piling on new ones. This dissertation proposes novel linguistic abstractions for the aforementioned design problems, offering ease of use, expressive power, strong guarantees, and good performance all at the same time. It introduces a new mechanism for generic programming, embodied in the Genus programming language. Genus adds expressive power and strengthens static checking, while handling common usage patterns simply. The power of Genus is then integrated into a second language design, Familia, that unifies several polymorphism mechanisms in a lightweight package. Evaluation suggests the design of Genus and Familia addresses the need for genericity and extensibility in developing large, complex software. This dissertation also introduces a new mechanism for exception handling. By allowing exceptions to tunnel through handlers, the design offers both the static assurance of checked exceptions and the flexibility of unchecked exceptions. This tunneling semantics is then generalized to a broader class of control effects to address a fundamental modularity problem: it prevents effect-polymorphic abstractions from handling effects by accident. This claim about abstraction safety is formally accounted for. We hope that the language-design ideas presented here will make their way into mainstream programming languages and help make it easier to write and reason about software.

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2019-08-30

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Computer science

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Myers, Andrew C.

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Kozen, Dexter Campbell
Selman, Bart
Tate, Ross Everett

Degree Discipline

Computer Science

Degree Name

Ph.D., Computer Science

Degree Level

Doctor of Philosophy

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Government Document

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dissertation or thesis

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