Abstract State Machines 1988-1998: Commented ASM Bibliography

An annotated bibliography of papers which deal with or use Abstract State Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm

ASMs and Operational Algorithmic Completeness of Lambda Calculus

We show that lambda calculus is a computation model which can step by step simulate any sequential deterministic algorithm for any computable function over integers or words or any datatype. More formally, given an algorithm above a family of computable functions (taken as primitive tools, i.e., kind of oracle functions for the algorithm), for every constant K big enough, each computation step of the algorithm can be simulated by exactly K successive reductions in a natural extension of lambda calculus with constants for functions in the above considered family. The proof is based on a fixed point technique in lambda calculus and on Gurevich sequential Thesis which allows to identify sequential deterministic algorithms with Abstract State Machines. This extends to algorithms for partial computable functions in such a way that finite computations ending with exceptions are associated to finite reductions leading to terms with a particular very simple feature.Comment: 37 page

Equivalence is in the Eye of the Beholder

In a recent provocative paper, Lamport points out "the insubstantiality of processes" by proving the equivalence of two different decompositions of the same intuitive algorithm by means of temporal formulas. We point out that the correct equivalence of algorithms is itself in the eye of the beholder. We discuss a number of related issues and, in particular, whether algorithms can be proved equivalent directly.Comment: See also the ASM web site at http://www.eecs.umich.edu/gasm

The Expressive Power of Abstract-State Machines

Conventional computation models assume symbolic representations of states and actions. Gurevich's Abstract-State Machine model takes a more liberal position: Any mathematical structure may serve as a state. This results in "a computational model that is more powerful and more universal than standard computation models". We characterize the Abstract-State Machine model as a special class of transition systems that widely extends the class of "computable" transition systems. This characterization is based on a fundamental Theorem of Y. Gurevich

Program Optimization Using Abstract State Machines

Usually the result code of source code by a compiler is not necessary the best one, and can be improved to run faster or to use less memory. This kind of improvement is done in compiling phase after parsing. Some good techniques in optimization are in folding the constants, elimination of dead code, or improvement of the loops. Here it is considered the runtime overhead and present how can this be improved. The source is specific for objectoriented languages with late binding, where a name of method to be called is bound to method dynamically. It increases the computation time by a cost of traversing the class hierarchy each time a method is called

Semantics of programming languages : a tool-oriented approach

By paying more attention to semantics-based tool generation, programming language semantics can significantly increase its impact. Ultimately, this may lead to ``Language Design Assistants\'\' incorporating substantial amounts of semantic knowledge