Software evolution and quality data from controlled, multiple, industrial case studies

A main difficulty to study the evolution and quality of real-life software systems is the effect of moderator factors, such as: programming skill, type of maintenance task, and learning effect. Experimenters must account for moderator factors to identify the relationships between the variables of interest. In practice, controlling for moderator factors in realistic (industrial) settings is expensive and rather difficult. The data presented in this paper has two particularities: First, it involves six professional developers and four real-life, industrial systems. Second, it was obtained from controlled, multiple case studies where the moderator variables: programming skill, maintenance task, and learning effect were controlled for. This data set is relevant to experimenters studying evolution and quality of real-life systems, in particular those interested in studying industrial systems and replicating empirical studies.