Functional programming languages have gained increasing popularity because of the expressive nature, ease of programming and strong resemblance to mathematics. Traditionally, compilers and interpreters for functional languages have not been able to compete with the existing procedural language counterparts. Often, the reason for not implementing a solution to a problem (especially for real time applications where response time is critical) in a functional programming language lies in the inefficient use of computer resources (such as CPU, memory, executable size, etc) by the interpreter, causing unacceptable delays and waste of resources. To address this problem, much work has been devoted to designing functional language interpreters (and compilers) that will perform computations and execute programs in comparable time (and resource usage) as code generated from procedural language compilers.
My research involves designing and implementing an abstract machine for charity. Abstract machines allows us to formally define and simulate different models of executing compiled charity code before implementing the machine in hardware. Using an abstract machine model also provides an inexpensive method to experiment and create an efficient means of executing charity code.
Dr. Robin Cockett, Tom Fukushima, Dave Spooner, Peter Vesely, Ulrich Hensel, Marc Schroeder, and Charles Tuckey.
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