Set Of Transformation Rules Research Articles

Description and improvement of iterative program transformations

Our framework is a programming method whose main idea consists in solving a problem statically and explicitly before taking some execution details into account. Within the framework of the methodology for constructing a program, we are often compelled to introduce intermediate values. We prove that in the case of sequential languages, and especially when they are sequence data types, those intermediates do not need to be effectively constructed. This aspect of the problem is obviously connected with efficiency. We suggest program transformation as a possible means of eliminating useless intermediates in the case of sequential languages. This paper follows [12] and aims at describing a program construction method, a set of transformations rules and their application with an example.

How to find Invariants for Coloured Petri Nets

This paper shows how invariants can be found for coloured Petri nets. We define a set of transformation rules, which can be used to transform the incidence-matrix, without changing the set of invariants.

A Transformational Derivation of a Parsing Algorithm in a High-Level Language

This paper presents a detailed algorithm derivation scenario, using correctness preserving source-to-source transfonnations. The algorithm derived is the Cocke-Younger nodal spans parsing algorithm. We describe a high-level SETL-like specification language, and give a partial correctness formalism and a set of transformation rules which enable the combination of algorithms whose partial correctness has already been established.

A tale of two structures: Underlying and surface forms in stories

A number of recent models of the structure of stories from the oral tradition have been couched in the form of ‘story grammars’, which describe the types of information that listeners expect to encounter in a story and the organization they tend to impose on that information. In the present paper, we argue that such analyses of story structure may complement analyses of sentence structure as a source of evidence concerning ways in which psychological processing needs constrain the form of complex serial productions. In addition, we present two major extensions of our earlier model of story structure (Mandler and Johnson 1977). First, the use of the base rules to characterize stories which consist of more than one episode is developed, and selection restrictions on the application of these rules are presented. Second, a set of transformational rules is proposed to account for meaning-preserving variations in the surface form of stories, and constraints on the nature of such rules are considered. Finally, we discuss criteria by which the observational and descriptive adequacy of models of story structure may be evaluated. We conclude that more traditional sources of evidence for evaluating grammars, such as intuitive judgments about well-formedness and constituent structure, must be supplemented with evidence based on the relation of the proposed structures to the details of psychological processing.

A training procedure for isolated word recognition systems

A procedure has been devised to reduce the amount of training required for a phoneme-based speaker-dependent word recognition system and still maintain performance. Each new speaker is required to provide utterances of only a fraction of the entire vocabulary as a training set. A set of transformation rules is used to estimate phoneme templates for the entire vocabulary from phoneme templates included in the training. The transformation rules are obtained in a pretraining procedure in which a group of speakers provides utterances of the entire vocabulary and multiple regression analysis (MRA) is used to obtain linear estimates of the entire phoneme template set in terms of the set designated as training templates. This group of speakers is generally distinct from the group of training speakers. Thus, since the transformation rules are established independent of the training speakers, the entire procedure can be considered a hybrid speaker-dependent/ speaker-independent system. Results of recognition experiments using spoken digits uttered by 30 male and female speakers and 67 airport names uttered by 30 male speakers have ascertained the effectiveness of this training procedure. A mean recognition accuracy of 98.2 percent was obtained for the latter utterance set after a 12-word training procedure.

The generative capacity of transformational grammars of ginsburg and partee

Any recursively enumerable language is generated by a transformational grammar with a type 3 base of trees and with no ordering or control device for the transformations. Furthermore, the set of transformation rules depends on the alphabet alone.