A Perspective on Automatic Programming

Abstract

Abstract 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. The perspective described here has resulted from the work of many people. Steve Smoliar, Stan Vestal, and especially Roger Duffey have been heavily involved in the design, implementation, and retrospective analysis of Φ0. Steve Smoliar and Roger Duffey have done detailed analyses of existing quantitative log interpretation software as well as several hypothetical syntheses. Paul Barth has been actively involved in the development of the model of programming for quantitative log interpretation described here; Steve Smoliar and Roger Duffey have contributed several key insights duringrr the process. Several of the interpretation developers at SDR have patiently and repeatedly explained the intricacies of log interpretation to us. Bruce Buchanan, Randy Davis, Elaine Kant, Tom Mitchell, and Reid Smith provided valuable feedback on earlier drafts of this paper.