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Empirical software engineering experts on the use of students and professionals in experiments
(2018)
Using students as participants remains a valid simplification of reality needed in laboratory contexts. It is an effective way to advance software engineering theories and technologies but, like any other aspect of study settings, should be carefully considered during the design, execution, interpretation, and reporting of an experiment. The key is to understand which developer population portion is being represented by the participants in an experiment. Thus, a proposal for describing experimental participants is put forward.
The relative pros and cons of using students or practitioners in experiments in empirical software engineering have been discussed for a long time and continue to be an important topic. Following the recent publication of “Empirical software engineering experts on the use of students and professionals in experiments” by Falessi, Juristo, Wohlin, Turhan, Münch, Jedlitschka, and Oivo (EMSE, February 2018) we received a commentary by Sjøberg and Bergersen. Given that the topic is of great methodological interest to the community and requires nuanced treatment, we invited two editorial board members, Martin Shepperd and Per Runeson, respectively, to provide additional views.
Context:
Test-driven development (TDD) is an agile software development approach that has been widely claimed to improve software quality. However, the extent to which TDD improves quality appears to be largely dependent upon the characteristics of the study in which it is evaluated (e.g., the research method, participant type, programming environment, etc.). The particularities of each study make the aggregation of results untenable.
Objectives:
The goal of this paper is to: increase the accuracy and generalizability of the results achieved in isolated experiments on TDD, provide joint conclusions on the performance of TDD across different industrial and academic settings, and assess the extent to which the characteristics of the experiments affect the quality-related performance of TDD.
Method:
We conduct a family of 12 experiments on TDD in academia and industry. We aggregate their results by means of meta-analysis. We perform exploratory analyses to identify variables impacting the quality-related performance of TDD.
Results:
TDD novices achieve a slightly higher code quality with iterative test-last development (i.e., ITL, the reverse approach of TDD) than with TDD. The task being developed largely determines quality. The programming environment, the order in which TDD and ITL are applied, or the learning effects from one development approach to another do not appear to affect quality. The quality-related performance of professionals using TDD drops more than for students. We hypothesize that this may be due to their being more resistant to change and potentially less motivated than students.
Conclusion:
Previous studies seem to provide conflicting results on TDD performance (i.e., positive vs. negative, respectively). We hypothesize that these conflicting results may be due to different study durations, experiment participants being unfamiliar with the TDD process, or case studies comparing the performance achieved by TDD vs. the control approach (e.g., the waterfall model), each applied to develop a different system. Further experiments with TDD experts are needed to validate these hypotheses.
