David Paul Nelson

Database: Enterprise, Skills and Innovation

Invited Paper.- Databases in Grid Applications: Locality and Distribution.- Spatio-temporal Databases.- Spatial Hierarchies and Topological Relationships in the Spatial MultiDimER Model.- Multidimensional Structures Dedicated to Continuous Spatiotemporal Phenomena.- TimeERplus: A Temporal EER Model Supporting Schema Changes.- Data Integration and Information Retrieval.- Semantically Rich Materialisation Rules for Integrating Heterogeneous Databases.- Answering Queries Using Views in the Presence of Functional Dependencies.- LAX: An Efficient Approximate XML Join Based on Clustered Leaf Nodes for XML Data Integration.- Exploitation of Referential Integrity Constraints for Efficient Update of Data Warehouse Views.- Correlation-Based Data Broadcasting in Wireless Networks.- Hierarchical Group-Based Sampling.- Using Schema Transformation Pathways for Data Lineage Tracing.- XML.- XDGL: XPath-Based Concurrency Control Protocol for XML Data.- Updating XML Using Object-Relational Database.- Applied Information Management.- Image Retrieval Using Weighted Color Co-occurrence Matrix.- Street Address Correction Based on Spelling Techniques.- Personalising Patient Information in the Real World.- Republishers in a Publish/Subscribe Architecture for Data Streams.

Experiences in deploying model-driven engineering

In this paper, we describe how Motorola has deployed model-driven engineering in product development, in particular for the development of highly reliable telecommunications systems, and outline the benefits obtained. Model-driven engineering has dramatically increased both the quality and the reliability of software developed in our organization, as well as the productivity of our software engineers. Our experience demonstrates that model-driven engineering significantly improves the development process for telecommunications systems. We discuss the elements we found most important for deployment of model-driven engineering in a large product development organization: An appropriate modeling language, a powerful domain-specific code generator, and a deployment support team.

Automated semantic analysis of design models

Based on several years of experience in generating code from large SDL and UML models in the telecommunications domain, it has become apparent that model analysis must be used to augment more traditional validation and testing techniques. While model correctness is extremely important, the difficulty of use and non-scalability of most formal verification techniques when applied to large-scale design models renders them insufficient for most applications. We have also repeatedly seen that even the most complete test coverage fails to find many problems. In contrast, sophisticated model analysis techniques can be applied without human interaction to large-scale models. A discussion of the model analysis techniques and the model defects that they can detect is provided, along with some real-world examples of defects that have been caught.