Generating Software for Well-Understood Domains

Authors Jacques Carette , Spencer W. Smith , Jason Balaci



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Author Details

Jacques Carette
  • Department of Computing and Software, McMaster University, Hamilton, Canada
Spencer W. Smith
  • Department of Computing and Software, McMaster University, Hamilton, Canada
Jason Balaci
  • Department of Computing and Software, McMaster University, Hamilton, Canada

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Jacques Carette, Spencer W. Smith, and Jason Balaci. Generating Software for Well-Understood Domains. In Eelco Visser Commemorative Symposium (EVCS 2023). Open Access Series in Informatics (OASIcs), Volume 109, pp. 7:1-7:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/OASIcs.EVCS.2023.7

Abstract

Current software development is often quite code-centric and aimed at short-term deliverables, due to various contextual forces (such as the need for new revenue streams from many individual buyers). We're interested in software where different forces drive the development. Well understood domains and long-lived software provide one such context.
A crucial observation is that software artifacts that are currently handwritten contain considerable duplication. By using domain-specific languages and generative techniques, we can capture the contents of many of the artifacts of such software. Assuming an appropriate codification of domain knowledge, we find that the resulting de-duplicated sources are shorter and closer to the domain. Our prototype, Drasil, indicates improvements to traceability and change management. We're also hopeful that this could lead to long-term productivity improvements for software where these forces are at play.

Subject Classification

ACM Subject Classification
  • Software and its engineering → Application specific development environments
  • Software and its engineering → Requirements analysis
  • Software and its engineering → Specification languages
  • Software and its engineering → Automatic programming
Keywords
  • code generation
  • document generation
  • knowledge capture
  • software engineering

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