Linguistic Reflection in Java

Reflective systems allow their own structures to be altered from within. Here we are concerned with a style of reflection, called linguistic reflection, which is the ability of a running program to generate new program fragments and to integrate these into its own execution. In particular we describe how this kind of reflection may be provided in the compiler-based, strongly typed object-oriented programming language Java. The advantages of the programming technique include attaining high levels of genericity and accommodating system evolution. These advantages are illustrated by an example taken from persistent programming which shows how linguistic reflection allows functionality (program code) to be generated on demand (Just-In-Time) from a generic specification and integrated into the evolving running program. The technique is evaluated against alternative implementation approaches with respect to efficiency, safety and ease of use.Comment: 25 pages. Source code for examples at http://www-ppg.dcs.st-and.ac.uk/Java/ReflectionExample/ Dynamic compilation package at http://www-ppg.dcs.st-and.ac.uk/Java/DynamicCompilation

GENUS : a generic component library for high level synthesis

This report describes the organization of GENUS, a generic component library for high level synthesis. Generic components and instances in GENUS are organized into hierarchical classes, with the component type stored at the root of the hierarchy, and particular instances stored at the leaves. This permits a consistent representation of generic components which may be used by a variety of synthesis and analysis tools. The appendix contains the description of the GENUS generator library

Speculative Staging for Interpreter Optimization

Interpreters have a bad reputation for having lower performance than just-in-time compilers. We present a new way of building high performance interpreters that is particularly effective for executing dynamically typed programming languages. The key idea is to combine speculative staging of optimized interpreter instructions with a novel technique of incrementally and iteratively concerting them at run-time. This paper introduces the concepts behind deriving optimized instructions from existing interpreter instructions---incrementally peeling off layers of complexity. When compiling the interpreter, these optimized derivatives will be compiled along with the original interpreter instructions. Therefore, our technique is portable by construction since it leverages the existing compiler's backend. At run-time we use instruction substitution from the interpreter's original and expensive instructions to optimized instruction derivatives to speed up execution. Our technique unites high performance with the simplicity and portability of interpreters---we report that our optimization makes the CPython interpreter up to more than four times faster, where our interpreter closes the gap between and sometimes even outperforms PyPy's just-in-time compiler.Comment: 16 pages, 4 figures, 3 tables. Uses CPython 3.2.3 and PyPy 1.

C++ Templates as Partial Evaluation

This paper explores the relationship between C++ templates and partial evaluation. Templates were designed to support generic programming, but unintentionally provided the ability to perform compile-time computations and code generation. These features are completely accidental, and as a result their syntax is awkward. By recasting these features in terms of partial evaluation, a much simpler syntax can be achieved. C++ may be regarded as a two-level language in which types are first-class values. Template instantiation resembles an offline partial evaluator. This paper describes preliminary work toward a single mechanism based on Partial Evaluation which unifies generic programming, compile-time computation and code generation. The language Catat is introduced to illustrate these ideas.Comment: 13 page