Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
Report from an Experiment: Impact of Documentation onMaintenance
Empirical Software Engineering
ICSE '76 Proceedings of the 2nd international conference on Software engineering
An Empirical Study on Using Stereotypes to Improve Understanding of UML Models
IWPC '04 Proceedings of the 12th IEEE International Workshop on Program Comprehension
Dynamic Coupling Measurement for Object-Oriented Software
IEEE Transactions on Software Engineering
The Elements of UML(TM) 2.0 Style
The Elements of UML(TM) 2.0 Style
Use of relative code churn measures to predict system defect density
Proceedings of the 27th international conference on Software engineering
An Experimental Investigation of Formality in UML-Based Development
IEEE Transactions on Software Engineering
The Impact of UML Documentation on Software Maintenance: An Experimental Evaluation
IEEE Transactions on Software Engineering
MoDELS '08 Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems
Empirical Analysis of the Relation between Level of Detail in UML Models and Defect Density
MoDELS '08 Proceedings of the 11th international conference on Model Driven Engineering Languages and Systems
Level of detail in UML models and its impact on model comprehension: A controlled experiment
Information and Software Technology
Evaluating the Impact of UML Modeling on Software Quality: An Industrial Case Study
MODELS '09 Proceedings of the 12th International Conference on Model Driven Engineering Languages and Systems
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The goal of this study is to investigate the use of UML and its impact on the change proneness of the implementation code. We look at whether the use of UML class diagrams, as opposed to using no modeling notation, influences code change proneness. Furthermore, using five design metrics we measure the quality of UML class diagrams and explore its correlation with code change proneness. Based on a UML model of an industrial system and multiple snapshots of the implementation code, we have found that at the system level the change proneness of code modeled using class diagrams is lower than that of code that is not modeled at all. However, we observe different results when performing the analysis at different system levels (e.g., subsystem and sub subsystem). Additionally, we have found significant correlations between class diagram size, complexity, and level of detail and the change proneness of the implementation code.