Why Research on Test-Driven Development is Inconclusive?

[Background] Recent investigations into the effects of Test-Driven Development (TDD) have been contradictory and inconclusive. This hinders development teams to use research results as the basis for deciding whether and how to apply TDD. [Aim] To support researchers when designing a new study and to increase the applicability of TDD research in the decision-making process in the industrial context, we aim at identifying the reasons behind the inconclusive research results in TDD. [Method] We studied the state of the art in TDD research published in top venues in the past decade, and analyzed the way these studies were set up. [Results] We identified five categories of factors that directly impact the outcome of studies on TDD. [Conclusions] This work can help researchers to conduct more reliable studies, and inform practitioners of risks they need to consider when consulting research on TDD.Comment: ESEM '20: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), October 8--9, 2020, Bari, Ital

Does the performance of TDD hold across software companies and premises?:a group of industrial experiments on TDD

Abstract Test-Driven Development (TDD) has been claimed to increase external software quality. However, the extent to which TDD increases external quality has been seldom studied in industrial experiments. We conduct four industrial experiments in two different companies to evaluate the performance of TDD on external quality. We study whether the performance of TDD holds across the premises of the same company and across companies. We identify participant-level characteristics impacting results. Iterative-Test Last (ITL), the reverse approach of TDD, outperforms TDD in three out of four premises. ITL outperforms TDD in both companies. The larger the experience with unit testing and testing tools, the larger the difference in performance between ITL and TDD (in favour of ITL). Technological environment (i.e., programming language and testing tool) seems not to impact results. Evaluating participant-level characteristics impacting results in industrial experiments may ease the understanding of TDD’s performance in realistic settings

A Family of Experiments on Test-Driven Development

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..