The design and implementation of Object Grammars

An Object Grammar is a variation on traditional BNF grammars, where the notation is extended to support declarative bidirectional mappings between text and object graphs. The two directions for interpreting Object Grammars are parsing and formatting. Parsing transforms text into an object graph by recognizing syntactic features and creating the corresponding object structure. In the reverse direction, formatting recognizes object graph features and generates an appropriate textual presentation. The key to Object Grammars is the expressive power of the mapping, which decouples the syntactic structure from the graph structure. To handle graphs, Object Grammars support declarative annotations for resolving textual names that refer to arbitrary objects in the graph structure. Predicates on the semantic structure provide additional control over the mapping. Furthermore, Object Grammars are compositional so that languages may be defined in a modular fashion. We have implemented our approach to Object Grammars as one of the foundations of the Ens (o) over bar system and illustrate the utility of our approach by showing how it enables definition and composition of domain-specific languages (DSLs). (C) 2014 Elsevier B.V. All rights reserved.</p

A Very High Level Logic Synthesis

The evolution of Computer Aided Design (CAD) calls for the incorporation of design specifications into a microelectronics system development cycle. This expansion requires the establishment of a new generation of CAD procedures, defined as Very High Level Logic Synthesis (VHLLS). The fundamental characteristics of open-ended VHLLS are: (1) front-end graphical interface; (2) time encapsulation; and (3) automatic translation into a behavioral description. Consequently, the VHLLS paradigm represents an advanced category of CAD-based microelectronics system design, built on a deep usage of expert systems and intelligent methods. Artificial Intelligence (AI) formalisms such as Knowledge Representation System (KRS) are necessary to model properties related to the very high level of specification such as: dealing with ambiguities and inconsistencies, reasoning, computing high-level specification, etc. A prototype VHLLS design suite, called Specification Procedure for Electronic Circuits in Automation Language (SPECIAL), is defined, compared with today\u27s commercial tools and verified using numerous design examples. As a result, a new family of formal and accelerated development methodologies has become feasible with a better understanding of formalized knowledge driving these design processes

DSM-PM2 adequacy for distributed constraint programming

As Redes de alta velocidade e o melhoramento rápido da performance dos microprocessadores fazem das redes de computadores um veículo apelativo para computação paralela. Não é preciso hardware especial para usar computadores paralelos e o sistema resultante é extensível e facilmente alterável. A programação por restrições é um paradigma de programação em que as relações entre as variáveis pode ser representada por restrições. As restrições diferem das primitivas comuns das outras linguagens de programação porque, ao contrário destas, não específica uma sequência de passos a executar mas antes a definição das propriedades para encontrar as soluções de um problema específico. As bibliotecas de programação por restrições são úteis visto elas não requerem que os programadores tenham que aprender novos skills para uma nova linguagem mas antes proporcionam ferramentas de programação declarativa para uso em sistemas convencionais. A tecnologia de Memoria Partilhada Distribuída (Distributed Shared Memory) apresenta-se como uma ferramenta para uso em aplicações distribuídas em que a informação individual partilhada pode ser acedida diretamente. Nos sistemas que suportam esta tecnologia os dados movem-se entre as memórias principais dos diversos nós de um cluster. Esta tecnologia poupa o programador às preocupações de passagem de mensagens onde ele teria que ter muito trabalho de controlo do comportamento do sistema distribuído. Propomos uma arquitetura orientada para a distribuição de Programação por Restrições que tenha os mecanismos da propagação e da procura local como base sobre um ambiente CC-NUMA distribuído usando memória partilhada distribuída. Os principais objetivos desta dissertação podem ser sumarizados em: - Desenvolver um sistema resolvedor de restrições, baseado no sistema AJ ACS [3], usando a linguagem ”C', linguagem nativa da biblioteca de desenvolvimento paralelo experimentada: O PM2 [4] - Adaptar, experimentar e avaliar a adequação deste sistema resolvedor de restrições usando DSM-PM2 [1] a um ambiente distribuído assente numa arquitetura CC-NUMA; /ABSTRACT - High-speed networks and rapidly improving microprocessor performance make networks of workstations an increasingly appealing vehicle for parallel computing. No special hardware is required to use this solution as a parallel computer, and the resulting system can be easily maintained, extended and upgraded. Constraint programming is a programming paradigm where relations between variables can be stated in the form of constraints. Constraints differ from the common primitives of other programming languages in that they do not specify a step or sequence of steps to execute but rather the properties of a solution to be found. Constraint programming libraries are useful as they do not require the developers to acquire skills for a new language, providing instead declarative programming tools for use within conventional systems. Distributed Shared Memory presents itself as a tool for parallel application in which individual shared data items can be accessed directly. In systems that support Distributed Shared Memory, data moves between main memories of different nodes. The Distributed Shared Memory spares the programmer the concerns of massage passing, where he would have to put allot of effort to control the distributed system behavior. We propose an architecture aimed for Distributed Constraint Programming Solving that relies on propagation and local search over a CC-NUMA distributed environment using Distributed Shared Memory. The main objectives of this thesis can be summarized as: - Develop a Constraint Solving System, based on the AJ ACS [3] system, in the C language, the native language of the experimented Parallel library - PM2 [4]; - Adapt, experiment and evaluate the developed constraint solving system distributed suitability by using DSM-PM2 [1] over a CC-NUMA architecture distributed environment

Nondeterminism in algebraic specifications and algebraic programs

"Nondeterminism in Algebraic Specifications and Algebraic Programs" presents a mathematical theory for the integration of three concepts: non-determinism, axiomatic specification and term rewriting. For non-deterministic programs, an algebraic specification language is provided which admits the application of automated tools based on term rewriting techniques. This general framework is used to explore connections between logic programming and algebraic programming. Examples from various areas of computer science are given, including results of computer experiments with a prototypical implementation. This book should be of interest to readers working within several fields of theoretical computer science, from algebraic specification theory to formal descriptions of distributed systems

A blackboard-based system for learning to identify images from feature data

A blackboard-based system which learns recognition rules for objects from a set of training examples, and then identifies and locates these objects in test images, is presented. The system is designed to use data from a feature matcher developed at R.S.R.E. Malvern which finds the best matches for a set of feature patterns in an image. The feature patterns are selected to correspond to typical object parts which occur with relatively consistent spatial relationships and are sufficient to distinguish the objects to be identified from one another. The learning element of the system develops two separate sets of rules, one to identify possible object instances and the other to attach probabilities to them. The search for possible object instances is exhaustive; its scale is not great enough for pruning to be necessary. Separate probabilities are established empirically for all combinations of features which could represent object instances. As accurate probabilities cannot be obtained from a set of preselected training examples, they are updated by feedback from the recognition process. The incorporation of rule induction and feedback into the blackboard system is achieved by treating the induced rules as data to be held on a secondary blackboard. The single recognition knowledge source effectively contains empty rules which this data can be slotted into, allowing it to be used to recognise any number of objects - there is no need to develop a separate knowledge source for each object. Additional object-specific background information to aid identification can be added by the user in the form of background checks to be carried out on candidate objects. The system has been tested using synthetic data, and successfully identified combinations of geometric shapes (squares, triangles etc.). Limited tests on photographs of vehicles travelling along a main road were also performed successfully