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

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Design Thinking Research

Part of the book series: Understanding Innovation ((UNDINNO))

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.

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Notes

  1. 1.

    You can access the archived materials used for conducting the experiment and the unprocessed and pre-processed data from https://doi.org/10.5281/zenodo.2540989.

  2. 2.

    See https://web.archive.org/web/20190115201202/http://wiki.wearedynamo.org/index.php/Guidelines_for_Academic_Requesters and https://web.archive.org/web/20190115201354/http://wiki.wearedynamo.org/index.php/Basics_of_how_to_be_a_good_requester).

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Correspondence to Patrick Rein .

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Rein, P., Taeumel, M., Hirschfeld, R. (2020). Towards Empirical Evidence on the Comprehensibility of Natural Language Versus Programming Language. In: Meinel, C., Leifer, L. (eds) Design Thinking Research . Understanding Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-28960-7_7

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