arXiv:1304.5257cs.SE
What Makes Code Hard to Understand?
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Abstract
What factors impact the comprehensibility of code? Previous research suggests that expectation-congruent programs should take less time to understand and be less prone to errors. We present an experiment in which participants with programming experience predict the exact output of ten small Python programs. We use subtle differences between program versions to demonstrate that seemingly insignificant notational changes can have profound effects on correctness and response times. Our results show that experience increases performance in most cases, but may hurt performance significantly when underlying assumptions about related code statements are violated.
As much as they are hated by some, there's empirical data indirectly suggesting that using curly braces for scoping might lead to less mistakes when reading code: > Similarly, the twospaces version of counting demonstrated that vertical space is more important then indentation…
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