物件導向軟體之架構(Object-Oriented Software Construction)探討

An approach to complexity theory which offers a means of analysing algorithms in terms of their tractability. The authors consider the problem in terms of parameterized languages and taking "k-slices" of the language, thus introducing readers to new classes of algorithms which may be analysed more precisely than was the case until now. The book is as self-contained as possible and includes a great deal of background material. As a result, computer scientists, mathematicians, and graduate students interested in the design and analysis of algorithms will find much of interest.

Parameterized Complexity

A type system is a syntactic method for automatically checking the absence of certain erroneous behaviors by classifying program phrases according to the kinds of values they compute. The study of type systems -- and of programming languages from a type-theoretic perspective -- has important applications in software engineering, language design, high-performance compilers, and security.This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.

https://www.seas.upenn.edu/~bcpierce/tapl/contents.pdf

Types and Programming Languages

Program analysis utilizes static techniques for computing reliable information about the dynamic behavior of programs. Applications include compilers (for code improvement), software validation (for detecting errors) and transformations between data representation (for solving problems such as Y2K). This book is unique in providing an overview of the four major approaches to program analysis: data flow analysis, constraint-based analysis, abstract interpretation, and type and effect systems. The presentation illustrates the extensive similarities between the approaches, helping readers to choose the best one to utilize.

Principles of program analysis

Functions, types and expressions programming languages and their operational semantics compilation partial evaluation of a flow chart languages partial evaluation of a first-order functional languages the view from Olympus partial evaluation of the Lambda calculus partial evaluation of prolog aspects of Similix - a partial evaluator for a subset of scheme partial evaluation of C applications of partial evaluation termination of partial evaluation program analysis more general program transformation guide to the literature the self-applicable scheme specializer.

Partial evaluation and automatic program generation

The Damas-Milner Calculus is the typed λ-calculus underlying the type system for ML and several other strongly typed polymorphic functional languages such as Miranda and Haskell. Mycroft has extended its problematic monomorphic typing rule for recursive definitions with a polymorphic typing rule. He proved the resulting type system, which we call the Milner-Mycroft Calculus, sound with respect to Milner's semantics, and showed that it preserves the principal typing property of the Damas-Milner Calculus. The extension is of practical significance in typed logic programming languages and, more generally, in any language with (mutually) recursive definitions

Type inference with polymorphic recursion

We present the dynamically typed A-calculus, an extension of the statically typed I-calculus with a special type Dyn and explicit dynamic type coercions corresponding to run-time type tagging and type check-and-untag operations. Programs in run-time typed languages can be interpreted in the dynamically typed L-calculus via a nondeterministic completion process that inserts explicit coercions and type declarations such that a well-typed term results. We characterize when two different completions of the same run-time typed program are coherent with an equational theory that is independent of an underlying I-theory. This theory is refined by orienting some equations to define safety and minimality of completions. Intuitively, a safe completion is one that does not produce an error at run-time which another completion would have avoided, and a minimal completion is a safe completion that executes fewest tagging and check-and-untag operations amongst all safe completions. We show that every untyped A-term has a safe completion at any type and that it is unique modulo a suitable congruence relation. Furthermore, we present a rewriting system for generating minimal completions. Assuming strong normalization of this rewriting system we show that every U-term has a minimal completion at any type, which is furthermore unique modulo equality in the dynamically typed A-calculus.

Dynamic typing: syntax and proof theory

We present new sound and complete axiomatizations of type equality and subtype inequality for a first-order type language with regular recursive types. The rules are motivated by coinductive characterizations of type containment and type equality via simulation and bisimulation, respectively. The main novelty of the axiomatization is the fixpoint rule (or coinduction principle). It states that from A,P $$\vdash$$ P one may deduce A $$\vdash$$ P, where P is either a type equality τ = τ' or type containment τ ≤ τ' and the proof of the premise must be contractive in a sense we define in this paper. In particular, a proof of A, P $$\vdash$$ P using the assumption axiom is not contractive. The fixpoint rule embodies a finitary coinduction principle and thus allows us to capture a coinductive relation in the fundamentally inductive framework of inference systems. The new axiomatizations are more concise than previous axiomatizations, particularly so for type containment since no separate axiomatization of type equality is required, as in Amadio and Cardelli's axiomatization. They give rise to a natural operational interpretation of proofs as coercions. In particular, the fixpoint rule corresponds to definition by recursion. Finally, the axiomatization is closely related to (known) efficient algorithms for deciding type equality and type containment. These can be modified to not only decide type equality and type containment, but also construct proofs in our axiomatizations efficiently. In connection with the operational interpretation of proofs as coercions this gives efficient (O(n 2) time) algorithms for constructing efficient coercions from a type to any of its supertypes or isomorphic types. More generally, we show how adding the fixpoint rule makes it possible to characterize inductively a set that is coinductively defined as the kernel (greatest fixed point) of an inference system.

Coinductive axiomatization of recursive type equality and subtyping

Binding-time analysis determines when variables and expressions in a program can be bound to their values, distinguishing between early (compile-time) and late (run-time) binding. Binding-time information can be used by compilers to produce more efficient target programs by partially evaluating programs at compile-time. Binding-time analysis has been formulated in abstract interpretation contexts and more recently in a type-theoretic setting.

Efficient type inference for higher-order binding-time analysis

Futhark is a purely functional data-parallel array language that offers a machine-neutral programming model and an optimising compiler that generates OpenCL code for GPUs. This paper presents the design and implementation of three key features of Futhark that seek a suitable middle ground with imperative approaches. First, in order to express efficient code inside the parallel constructs, we introduce a simple type system for in-place updates that ensures referential transparency and supports equational reasoning. Second, we furnish Futhark with parallel operators capable of expressing efficient strength-reduced code, along with their fusion rules. Third, we present a flattening transformation aimed at enhancing the degree of parallelism that (i) builds on loop interchange and distribution but uses higher-order reasoning rather than array-dependence analysis, and (ii) still allows further locality-of-reference optimisations. Finally, an evaluation on 16 benchmarks demonstrates the impact of the language and compiler features and shows application-level performance competitive with hand-written GPU code.

Fritz Henglein

Papers

Type inference with polymorphic recursion

Dynamic typing: syntax and proof theory

Coinductive axiomatization of recursive type equality and subtyping

Efficient type inference for higher-order binding-time analysis

Futhark: purely functional GPU-programming with nested parallelism and in-place array updates