Refactoring pattern matching

Meng Wang, Jeremy Gibbons, Kazutaka Matsuda, Zhenjiang Hu

Research output: Contribution to journalArticle (Academic Journal)peer-review

17 Citations (Scopus)
6 Downloads (Pure)

Abstract

Defining functions by pattern matching over the arguments is advantageous for understanding and reasoning, but it tends to expose the implementation of a datatype. Significant effort has been invested in tackling this loss of modularity; however, decoupling patterns from concrete representations while maintaining soundness of reasoning has been a challenge. Inspired by the development of invertible programming, we propose an approach to program refactoring based on a right-invertible language rinv—every function has a right (or pre-) inverse. We show how this new design is able to permit a smooth incremental transition from programs with algebraic datatypes and pattern matching, to ones with proper encapsulation, while maintaining simple and sound reasoning.

Original languageEnglish
JournalScience of Computer Programming
Volume78
Issue number11
DOIs
Publication statusPublished - 2012

Research Groups and Themes

  • Programming Languages

Keywords

  • Functional programming
  • Refactoring
  • Pattern matching
  • Invertible programming
  • Abstract datatypes
  • Fusion

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