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Title: An external replication on the effects of test-driven development using a multi-site blind analysis approach
Authors: Fucci, D
Scanniello, G
Romano, S
Shepperd, M
Sigweni, B
Uyaguari, F
Turhan, B
Juristo, N
Oivo, M
Keywords: Test-driven development;External experiment replication;blind analysis
Issue Date: 2016
Publisher: ACM
Citation: International Symposium on Empirical Software Engineering and Measurement (ESEM), 2016, 08-09-September-2016
Abstract: Context: Test-driven development (TDD) is an agile practice claimed to improve the quality of a software product, as well as the productivity of its developers. A previous study (i.e., baseline experiment) at the University of Oulu (Finland) compared TDD to a test-last development (TLD) approach through a randomized controlled trial. The results failed to support the claims. Goal: We want to validate the original study results by replicating it at the University of Basilicata (Italy), using a different design. Method: We replicated the baseline experiment, using a crossover design, with 21 graduate students. We kept the settings and context as close as possible to the baseline experiment. In order to limit researchers bias, we involved two other sites (UPM, Spain, and Brunel, UK) to conduct blind analysis of the data. Results: The Kruskal-Wallis tests did not show any significant difference between TDD and TLD in terms of testing effort (p-value = .27), external code quality (p-value = .82), and developers' productivity (p-value = .83). Nevertheless, our data revealed a difference based on the order in which TDD and TLD were applied, though no carry over effect. Conclusions: We verify the baseline study results, yet our results raises concerns regarding the selection of experimental objects, particularly with respect to their interaction with the order in which of treatments are applied. We recommend future studies to survey the tasks used in experiments evaluating TDD. Finally, to lower the cost of replication studies and reduce researchers' bias, we encourage other research groups to adopt similar multi-site blind analysis approach described in this paper.
ISBN: 9781450344272
ISSN: 1949-3770
Appears in Collections:Dept of Computer Science Research Papers

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