A Programming Language Supporting First-Class Parallel Environments
MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR COMPUTER SCIENCE
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This thesis presents a new programming model called the symmetric model in which the representation of programs is identical to the representation of data to specify a computation, one defines a data structure. This data structure possesses the semantics of a first-class naming environment-it defines a scope and can be used to affect the evaluation environment of other expressions. We present a new programming language called Symmetric Lisp based on the symmetric model. Program structures in Symmetric Lisp are considered non- strict a programs components may be examined even as its other elements continue to evaluate. The first part of the thesis investigates the interaction of non-strictness with first-class naming environments. The second part of the thesis discuss the compilation and implementation of Symmetric Lisp. We present an extended type-inference system for first-class environments that can be used to infer the proper evaluation environment of identifiers found within the scope of environment-yielding expressions. We also present a translation of Symmetric Lisp into a high-level data flow language.
- Computer Programming and Software