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Details of Grant 

EPSRC Reference: GR/L28296/01
Title: XSLAM - THE EXPLICIT SUBSTITUTION LINEAR ABSTRACT MACHINE
Principal Investigator: Ritter, Dr E
Other Investigators:
Ghani, Professor N De Paiva, Dr V
Researcher Co-Investigators:
Project Partners:
Department: School of Computer Science
Organisation: University of Birmingham
Scheme: Standard Research (Pre-FEC)
Starts: 01 January 1997 Ends: 31 March 2000 Value (£): 131,598
EPSRC Research Topic Classifications:
Artificial Intelligence
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:  
Summary on Grant Application Form
The advantages of functional programming are well-known: programs are easier to write, understand and verify than their imperative counterparts, and are thus easier to maintain. However, functional languages are more memory intensive and these problems have hindered the wider use of functional programming in industry. To reduce the excessive demands on memory and increase efficiency of computation, the handling of garbage collection and sharing in functional languages must be improved.The goal of this project is to use recent advances in the foundations of functional programming to construct and implement efficient abstract machines. We will combine recent developments in linear logic and explicit substitutions to increase control over memory allocation and thus avoid waste of memory and unnecessary duplication of computation steps. Moreover, our use of solid theoretical foundations not only guides the design of the machines but also ensures their correctness. As a further beneficial side effect we hope to get a theoretical explanation of optimal reductions via their relationship to explicit substitutions.
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Further Information:  
Organisation Website: http://www.bham.ac.uk