A Programming Language Supporting First-Class Parallel Environments

Abstract

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 program's 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.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1989
Accession Number
ADA207833

Entities

People

  • Suresh Jagannathan

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Application Software
  • Artificial Intelligence
  • Computer Programming
  • Computer Science
  • Computers
  • Expert Systems
  • Hemorrhagic Shock
  • High Level Language Architecture
  • High Level Languages
  • Information Systems
  • Lisp Programming Language
  • Operating Systems
  • Prime Numbers
  • Programming Languages
  • Resource Management
  • Shell Scripts
  • Side Effects

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Calculus or Mathematical Analysis
  • Computer Science.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms