End-user programming as translation: An experimental framework and study

One of the reputed advantages of end-user programming languages is that they support a given problem domain with a set of programming abstractions that are "just right" for the end-users who need to program within that domain. Green and Petre's [1] Cognitive Dimensions Framework accounts for this advantage in terms of the "closeness of mapping" dimension: the closer the programming domain is to the problem domain, the easier the programming task. This suggests that programming might be conceptualized as a process of translation, with "close" translations being more efficient and error-free than "distant" ones. While there appears to be a strong intuitive basis for this view, there presently exists little direct empirical evidence. To that end, we present an experimental framework for systematically exploring the "closeness of mapping" dimension within the programming domain of college-level textbook algorithms and data structures. A pilot study we conducted within that framework provides preliminary evidence in support of one of our hypotheses.