Context: There is a lack of empirical evidence on the differences between model-driven development (MDD), where code is automatically derived from conceptual models, and traditional software development method, where code is manually written. In our previous work, we compared both methods in a baseline experiment concluding that quality of the software developed following MDD was significantly better only for more complex problems (with more function points). Quality was measured through test cases run on a functional system. Objective: This paper reports six replications of the baseline to study the impact of problem complexity on software quality in the context of MDD. Method: We conducted replications of two types: strict replications and object replications. Strict replications were similar to the baseline, whereas we used more complex experimental objects (problems) in the object replications. Results: MDD yields better quality independently of problem complexity with a moderate effect size. This effect is bigger for problems that are more complex. Conclusions: Thanks to the bigger size of the sample after aggregating replications, we discovered an effect that the baseline had not revealed due to the small sample size. The baseline results hold, which suggests that MDD yields better quality for more complex problems.

中文翻译：

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在质量方面评估模型驱动的开发声明：一系列实验

背景：模型驱动开发 (MDD)（代码自动从概念模型派生）与传统软件开发方法（手动编写代码）之间的差异缺乏经验证据。在我们之前的工作中，我们在基线实验中比较了两种方法，得出的结论是，遵循 MDD 开发的软件的质量仅在处理更复杂的问题（具有更多功能点）时才明显更好。质量是通过在功能系统上运行的测试用例来衡量的。目标：本文报告了基线的六次复制，以研究 MDD 背景下问题复杂性对软件质量的影响。方法：我们进行了两种类型的复制：严格复制和对象复制。严格复制与基线相似，而我们在对象复制中使用了更复杂的实验对象（问题）。结果：MDD 产生更好的质量，不受问题复杂性的影响，效果大小适中。对于更复杂的问题，这种影响更大。结论：由于聚合重复后样本量更大，我们发现了基线由于样本量小而未显示的效果。基线结果成立，这表明 MDD 为更复杂的问题产生更好的质量。我们发现了一种由于样本量小而基线未显示的效果。基线结果成立，这表明 MDD 为更复杂的问题产生更好的质量。我们发现了一种由于样本量小而基线未显示的效果。基线结果成立，这表明 MDD 为更复杂的问题产生更好的质量。