TY - JOUR
T1 - Considerations and Pitfalls for Reducing Threats to the Validity of Controlled Experiments on Code Comprehension
AU - Feitelson, Dror G.
N1 - Publisher Copyright: © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/11
Y1 - 2022/11
N2 - Understanding program code is a complicated endeavor. As a result, studying code comprehension is also hard. The prevailing approach for such studies is to use controlled experiments, where the difference between treatments sheds light on factors which affect comprehension. But it is hard to conduct controlled experiments with human developers, and we also need to find a way to operationalize what “comprehension” actually means. In addition, myriad different factors can influence the outcome, and seemingly small nuances may be detrimental to the study’s validity. In order to promote the development and use of sound experimental methodology, we discuss both considerations which need to be applied and potential problems that might occur, with regard to the experimental subjects, the code they work on, the tasks they are asked to perform, and the metrics for their performance. A common thread is that decisions that were taken in an effort to avoid one threat to validity may pose a larger threat than the one they removed.
AB - Understanding program code is a complicated endeavor. As a result, studying code comprehension is also hard. The prevailing approach for such studies is to use controlled experiments, where the difference between treatments sheds light on factors which affect comprehension. But it is hard to conduct controlled experiments with human developers, and we also need to find a way to operationalize what “comprehension” actually means. In addition, myriad different factors can influence the outcome, and seemingly small nuances may be detrimental to the study’s validity. In order to promote the development and use of sound experimental methodology, we discuss both considerations which need to be applied and potential problems that might occur, with regard to the experimental subjects, the code they work on, the tasks they are asked to perform, and the metrics for their performance. A common thread is that decisions that were taken in an effort to avoid one threat to validity may pose a larger threat than the one they removed.
KW - Code comprehension
KW - Controlled experiment
KW - Experimental methodology
KW - Threats to validity
UR - http://www.scopus.com/inward/record.url?scp=85132581760&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s10664-022-10160-3
DO - https://doi.org/10.1007/s10664-022-10160-3
M3 - مقالة
SN - 1382-3256
VL - 27
JO - Empirical Software Engineering
JF - Empirical Software Engineering
IS - 6
M1 - 123
ER -