An introduction to Graph Data Management

A graph database is a database where the data structures for the schema and/or instances are modeled as a (labeled)(directed) graph or generalizations of it, and where querying is expressed by graph-oriented operations and type constructors. In this article we present the basic notions of graph databases, give an historical overview of its main development, and study the main current systems that implement them

Three Dimensional Software Modelling

Traditionally, diagrams used in software systems modelling have been two dimensional (2D). This is probably because graphical notations, such as those used in object-oriented and structured systems modelling, draw upon the topological graph metaphor, which, at its basic form, receives little benefit from three dimensional (3D) rendering. This paper presents a series of 3D graphical notations demonstrating effective use of the third dimension in modelling. This is done by e.g., connecting several graphs together, or in using the Z co-ordinate to show special kinds of edges. Each notation combines several familiar 2D diagrams, which can be reproduced from 2D projections of the 3D model. 3D models are useful even in the absence of a powerful graphical workstation: even 2D stereoscopic projections can expose more information than a plain planar diagram

Towards rule-based visual programming of generic visual systems

This paper illustrates how the diagram programming language DiaPlan can be used to program visual systems. DiaPlan is a visual rule-based language that is founded on the computational model of graph transformation. The language supports object-oriented programming since its graphs are hierarchically structured. Typing allows the shape of these graphs to be specified recursively in order to increase program security. Thanks to its genericity, DiaPlan allows to implement systems that represent and manipulate data in arbitrary diagram notations. The environment for the language exploits the diagram editor generator DiaGen for providing genericity, and for implementing its user interface and type checker.Comment: 15 pages, 16 figures contribution to the First International Workshop on Rule-Based Programming (RULE'2000), September 19, 2000, Montreal, Canad

Automatic view schema generation in object-oriented databases

An object-oriented data schema is a complex structure of classes interrelated via generalization and property decomposition relationships. We define an object-oriented view to be a virtual schema graph with possibly restructured generalization and decomposition hierarchies - rather than just one individual virtual class as proposed in the literature. In this paper, we propose a methodology, called MultiView, for supporting multiple such view schemata. MultiView is anchored on the following complementary ideas: (a) the view definer derives virtual classes and then integrates them into one consistent global schema graph and (b) the view definer specifies arbitrarily complex view schemata on this augmented global schema. The focus of this paper is, however, on the second, less explored, issue. This part of the view definition is performed using the following two steps: (1) view class selection and (2) view schema graph generation. For the first, we have developed a view definition language that can be used by the view definer to specify the selection of the desired view classes from the global schema. For the second, we have developed two algorithms that automatically augment the set of selected view classes to generate a complete, minimal and consistent view class generalization hierarchy. The first algorithm has linear complexity but it assumes that the global schema graph is a tree. The second algorithm overcomes this restricting assumption and thus allows for multiple inheritance, but it does so at the cost of a higher complexity

Exploiting the Hierarchical Structure of Rule-Based Specifications for Decision Planning

Rule-based specifications have been very successful as a declarative approach in many domains, due to the handy yet solid foundations offered by rule-based machineries like term and graph rewriting. Realistic problems, however, call for suitable techniques to guarantee scalability. For instance, many domains exhibit a hierarchical structure that can be exploited conveniently. This is particularly evident for composition associations of models. We propose an explicit representation of such structured models and a methodology that exploits it for the description and analysis of model- and rule-based systems. The approach is presented in the framework of rewriting logic and its efficient implementation in the rewrite engine Maude and is illustrated with a case study.

BDEF : the behavioral design data exchange format

BDDB is a Behavioral Design Data Base that manages the design data produced and consumed by different behavioral synthesis tools. These different design tools retrieve design data from BDDB, manipulate the data, and then store the results back into the data base. BDDB thus needs to address the following two issues: (1) a design data exchange approach and (2) customized design data interfaces. To address the first issue, we have developed a textual description format for describing design data objects and relationships. This language, referred to as the Behavioral Design Data Exchange Format (BDEF), is used as common format for exchanging design data between BDDB and the design tools in the behavioral synthesis environment. To address the second issue, we have developed a behavioral object type description language (generally referred to as schema definition language) for describing the global data structures required by design tools as well as the desired design subviews of this global BDDB design information. One design view class, namely, BDEF, is the topic of this report.In this report we give a formal definition of the BDEF format. Then we describe a comprehensive example of applying BDEF to the behavioral synthesis domain. That is, we present the complete BDEF syntax for the Extended Control/Data Flow Graph Model (ECDFG), which is the design representation model used by most behavioral synthesis tools in the UCI CADLAB synthesis system. We also present several example descriptions of designs using this ECDFG model. A parser/graph compiler from BDEF into the generalized ECDFG design representation as well as a BDEF generator from the ECDFG data structures into the BDEF format have been implemented

Knowledge formalization in experience feedback processes : an ontology-based approach

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

A design representation model for high-level synthesis

Design tools share and exchange various types of information pertaining to the design. The identification of a uniform design representation to capture this information is essential for the development of a successful design environment. We have done an extensive study on the representation needs of existing database tools in the UCI CADLAB; examples of which are graph compilers for high-level hardware specifications, state schedulers, hardware allocators, and microarchitecture optimizers. The result of this study is the development of a design representation model that will serve as a common internal representation (DDM) for all system and behavioral synthesis tools. DDM thus builds the foundation for a CAD Framework in which design tools can communicate via operating on this common representation. The design information is composed of three separate graph models: the conceptual model, the behavioral model and the structural model. The conceptual model (represented by a Design Entity Graph) captures the overall organization of the design information, such as, versions and configurations. The behavioral model (represented by an Augmented Control/Data Flow Graph) describes the design behavior. The structural model (represented by an Annotated Component Graph) captures the hierarchical data path structure and its geometric information. In this paper, we define the last two graph models. They both capture the actual design data of the application domain. Since VHDL has gained increasing popularity as hardware description language for synthesis, we give numerous examples throughout this report that show how the proposed design representation model can be used to represent VHDL specifications