Why Is Programming (Sometimes) So Difficult? Programming as Scientific Discovery in Multiple Problem Spaces

Jinwoo Kim and F. Javier Lerch
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Jinwoo Kim: Department of Business Administration, Yonsei University, Seoul, 120-749, Korea
F. Javier Lerch: Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213

Information Systems Research, 1997, vol. 8, issue 1, 25-50

Abstract: Our theoretical framework views programming as search in three problem spaces: rule, instance, and representation. The main objectives of this study are to find out how programmers change representation while working in multiple problem spaces, and how representation change increases the difficulty of programming tasks. Our theory of programming indicates that programming is similar to the way scientists discover and test theories. That is, programmers generate hypotheses in the rule space and test these hypotheses in the instance space. Moreover, programmers change their representations in the representation space when rule development becomes too difficult or alternative representations are available. We conducted three empirical studies with different programming tasks: writing a new program, understanding an existing program, and reusing an old program. Our results indicate that considerable cognitive difficulties stem from the need to change representations in these tasks. We conclude by discussing the implications of viewing programming as a scientific discovery for the design of programming environments and training methods.

Keywords: empirical studies of programmers; object-oriented programming; scientific discovery; multiple problem spaces (search for similar items in EconPapers)
Date: 1997
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