IEEE Transactions on Software Engineering, 11:1321-36

Most work in automatic programming has focused primarily on the roles of deduction and programming knowledge. However, the role played by knowledge of the task domain seems to be at least as important, both for the usability of an automatic programming system and for the feasibility of building one which works on non-trivial problems. This perspective has evolved during the course of a variety of studies over the last several years, including detailed examination of existing software for a particular domain (quantitative interpretation of oil well logs) and the implementation of an experimental automatic programming system for that domain. The importance of domain knowledge has two important implications: a primary goal of automatic programming research should be to characterize the programming process for specific domains; and a crucial issue to be addressed in these characterizations is the interaction of domain and programming knowledge during program synthesis.

Most work in automatic programming has focused primarily on the roles of deduction and programming knowledge. However, the role played by knowledge of the task domain seems to be at least as important, both for the usability of an automatic programming system and for the feasibility of building one which works on non-trivial problems. This perspective has evolved during the course of a variety of studies over the last several years, including detailed examination of existing software for a particular domain (quantitative interpretation of oil well logs) and the implementation of an experimental automatic programming system for that domain. The importance of domain knowledge has two important implications: a primary goal of automatic programming research should be to characterize the programming process for specific domains; and a crucial issue to be addressed in these characterizations is the interaction of domain and programming knowledge during program synthesis.

New York: Elsevier-North Holland

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This paper presents a framework for characterizing automatic programming systems in terms of how a task is communicated to the system, the method and time at which the system acquires the knowledge to perform the task, and the characteristics of the resulting program to perform that task. It describes one approach In which both tasks and knowledge about the task domain are stated in natural language In the terms of that domain. All knowledge of computer science necessary to implement the task is internalized inside the system.In IJCAI-73: THIRD INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 20-23 August 1973, Stanford University Stanford, California, pp.494-499

Proceedings of the Symposium on the Mechanisation of Thought Processes.Teddington, Middlesex, England: National Physical Laboratory.

From the The Teddington Conference– D. V. Blake and A. M. Uttley (Eds.). Proceedings of the Symposium on Mechanisation of Thought Processes, National Physical Laboratory, Teddington, Middlesex, England, London: H. M. Stationary Office.