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Towards Empirical Evidence on the Comprehensibility of Natural Language Versus Programming Language

In: Design Thinking Research

Author

Listed:
  • Patrick Rein

    (Hasso Plattner Institute for Digital Engineering)

  • Marcel Taeumel

    (Hasso Plattner Institute for Digital Engineering)

  • Robert Hirschfeld

    (Hasso Plattner Institute for Digital Engineering)

Abstract

In software design teams, communication between programmers and non-programming domain experts is an ongoing challenge. In this communication, source code documents could be a valuable artifact as they describe domain logic in an unambiguous way. Some programming languages, such as the Smalltalk programming language, try to make source code accessible. Its concise syntax and message-passing semantics are so close to basic English, that it is likely to appeal to even non-programming domain experts. However, the inherent obscurity of technical programming details still poses a significant burden for text comprehension. We conducted a code-reading study in form of a questionnaire through Amazon Mechanical Turk and SurveyMonkey. The results indicate that even in simple problem domains, a simple English text is more comprehensive than a simple Smalltalk program. Consequently, source code in its current text form should not be used as a reliable communication medium between programmers and (non-programming) domain experts.

Suggested Citation

  • Patrick Rein & Marcel Taeumel & Robert Hirschfeld, 2020. "Towards Empirical Evidence on the Comprehensibility of Natural Language Versus Programming Language," Understanding Innovation, in: Christoph Meinel & Larry Leifer (ed.), Design Thinking Research, pages 111-131, Springer.
    • Handle: RePEc:spr:undchp:978-3-030-28960-7_7
    DOI: 10.1007/978-3-030-28960-7_7
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