Using qualitative data analysis (QDA) to perform domain analysis and modeling has shown great promise. Yet, the evaluation of such approaches has been limited to single-case case studies. While these exploratory cases are valuable for an initial assessment, the evaluation of the efficacy of QDA to solve the suggested problems is restricted by the common single-case case study research design. Using our own method, called QDAcity-RE, as the example, we present an in-depth empirical evaluation of employing qualitative data analysis for domain modeling using a controlled experiment design. Our controlled experiment shows that the QDA-based method leads to a deeper and richer set of domain concepts discovered from the data, while also being more time efficient than the control group using a comparable non-QDA-based method with the same level of traceability.

使用定性数据分析 (QDA) 进行领域分析和建模已显示出巨大的前景。然而，对此类方法的评估仅限于单个案例研究。虽然这些探索性案例对于初步评估很有价值，但对 QDA 解决建议问题的有效性的评估受到常见的单一案例研究设计的限制。使用我们自己的方法，称为 QDAcity-RE，作为示例，我们使用受控实验设计对使用定性数据分析进行域建模进行了深入的实证评估。我们的受控实验表明，基于 QDA 的方法可以从数据中发现更深入、更丰富的领域概念，