A framework for incremental progress in the application of AI to software engineering

  • Authors:
  • Guillermo Arango;Ira Baxter;Peter Freeman

  • Affiliations:
  • University of California, Irvine;University of California, Irvine;University of California, Irvine

  • Venue:
  • ACM SIGSOFT Software Engineering Notes
  • Year:
  • 1988

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Abstract

The study of the potential contributions of artificial intelligence (AI) to software engineering (SE) needs a conceptual framework within which to analyze the scope and feasibility of such contributions.We propose a framework designed to uncover opportunities for incremental progress in SE through the adoption of AI solutions. We emphasize incremental for we believe progress must be assessed in terms of discrete, well-defined steps. The incremental approach involves two fundamental steps:1. partition the universe into restricted domains of study, and2. examine each of those domains to determine what progress is possible.The framework can be used as a guideline for refining research domains, as a context for comparing applications, or as a mechanism to provide structure for future discussions of applications of AI to SE.