Description and Optimization of Abstract Machines in a Dialect of Prolog

In order to achieve competitive performance, abstract machines for Prolog and related languages end up being large and intricate, and incorporate sophisticated optimizations, both at the design and at the implementation levels. At the same time, efficiency considerations make it necessary to use low-level languages in their implementation. This makes them laborious to code, optimize, and, especially, maintain and extend. Writing the abstract machine (and ancillary code) in a higher-level language can help tame this inherent complexity. We show how the semantics of most basic components of an efficient virtual machine for Prolog can be described using (a variant of) Prolog. These descriptions are then compiled to C and assembled to build a complete bytecode emulator. Thanks to the high level of the language used and its closeness to Prolog, the abstract machine description can be manipulated using standard Prolog compilation and optimization techniques with relative ease. We also show how, by applying program transformations selectively, we obtain abstract machine implementations whose performance can match and even exceed that of state-of-the-art, highly-tuned, hand-crafted emulators.Comment: 56 pages, 46 figures, 5 tables, To appear in Theory and Practice of Logic Programming (TPLP

Observation and abstract behaviour in specification and implementation of state-based systems

Classical algebraic specification is an accepted framework for specification. A criticism which applies is the fact that it is functional, not based on a notion of state as most software development and implementation languages are. We formalise the idea of a state-based object or abstract machine using algebraic means. In contrast to similar approaches we consider dynamic logic instead of equational logic as the framework for specification and implementation. The advantage is a more expressive language allowing us to specify safety and liveness conditions. It also allows a clearer distinction of functional and state-based parts which require different treatment in order to achieve behavioural abstraction when necessary. We shall in particular focus on abstract behaviour and observation. A behavioural notion of satisfaction for state-elements is needed in order to abstract from irrelevant details of the state realisation

Solving the TTC 2011 Reengineering Case with GrGen.NET

The challenge of the Reengineering Case is to extract a state machine model out of the abstract syntax graph of a Java program. The extracted state machine offers a reduced view on the full program graph and thus helps to understand the program regarding the question of interest. We tackle this task employing the general purpose graph rewrite system GrGen.NET (www.grgen.net).Comment: In Proceedings TTC 2011, arXiv:1111.440

Lazy Evaluation and Delimited Control

The call-by-need lambda calculus provides an equational framework for reasoning syntactically about lazy evaluation. This paper examines its operational characteristics. By a series of reasoning steps, we systematically unpack the standard-order reduction relation of the calculus and discover a novel abstract machine definition which, like the calculus, goes "under lambdas." We prove that machine evaluation is equivalent to standard-order evaluation. Unlike traditional abstract machines, delimited control plays a significant role in the machine's behavior. In particular, the machine replaces the manipulation of a heap using store-based effects with disciplined management of the evaluation stack using control-based effects. In short, state is replaced with control. To further articulate this observation, we present a simulation of call-by-need in a call-by-value language using delimited control operations

State machines for large scale computer software and systems

A method for specifying the behavior and architecture of discrete state systems such as digital electronic devices and software using deterministic state machines and automata products. The state machines are represented by sequence maps $f:A^*\to X$ where $f(s)=x$ indicates that the output of the system is $x$ in the state reached by following the sequence of events $s$ from the initial state. Examples provided include counters, networks, reliable message delivery, real-time analysis of gates and latches, and producer/consumer. Techniques for defining, parameterizing, characterizing abstract properties, and connecting sequence functions are developed. Sequence functions are shown to represent (possibly non-finite) Moore type state machines and general products of state machines. The method draws on state machine theory, automata products, and recursive functions and is ordinary working mathematics, not involving formal methods or any foundational or meta-mathematical techniques. Systems in which there are levels of components that may operate in parallel or concurrently are specified in terms of function composition