Abstracts

Dr Gavin Bierman

An Introduction to Object Databases

This talk will be a non-technical introduction to object databases. I will give some reasons why i think it is worth reconsidering relational database technology, and show how object databases can help. In particular I will discuss the work of the ODMG (Object Data Management Group) in defining a standard for persistance of objects in databases. I will also mention work in thw Opera Group in Cambridge involving the ODMG standard.

Don Syme

An Overview of .NET Common Language Runtime Research at MSR Cambridge

The .NET Common Language Runtime (CLR) provides services for the execution of software, e.g. JIT compilation and garbage collection. As the name suggests, it has been designed to support a range of programming languages and to help them interoperate. MSR Cambridge have been involved with the platform since mid 1998, analysing the design, writing compilers for the platform and proposing extensions to the design. Several significant research projects are currently underway, and this talk will give an overview of these. The projects include:

o A formal description and analysis of the verification rules for the CLR's intermediary language, MS-IL (Gordon and Syme);

o The design and implementation of support for polymorphism in the CLR (Kennedy & Syme);

o The implementation of compilers for Haskell (Syme & Thomas) and Standard ML (Benton & Kennedy), along with language-specific extensions for better interoperability;

o The design and implementation of MS-ILX, an extended version of MS-IL with support for closures, polymorphism and algebraic datatypes (Syme).

This talk will outline what we're covering in these projects from at a high-level, explaining how they fit together in the wider scheme of things.

Ann Copestake

Defaults and Probabilities

Many approaches to natural language processing use probabilities, some use defaults and a few involve both. I'll discuss some applications of default inheritance and nonmonotonic logics in formalizing models of language and contrast these with cases where probabilistic models are more appropriate. I'll aim to show that, although it isn't always straightforward to decide which sort of approach to use, there are clear differences in applicability, and that we really do need both probabilities and defaults.