Ogenrwot, DanielNakatumba-Nabende, JoyceChaudron, Michel R.V.2022-12-292022-12-292021Ogenrwot, D., Nakatumba-Nabende, J., & Chaudron, M. R. (2021). Integration of design smells and role-stereotypes classification dataset. Data in Brief, 36, 107125. https://doi.org/10.1016/j.dib.2021.107125https://doi.org/10.1016/j.dib.2021.107125https://nru.uncst.go.ug/handle/123456789/6742Design smells are recurring patterns of poorly designed (fragments of) software systems that may hinder main- tainability. Role-stereotypes indicate generic responsibilities that classes play in system design. Although the concepts of role-stereotypes and design smells are widely divergent, both are significant contributors to the design and mainte- nance of software systems. To improve software design and maintainability, there is a need to understand the relation- ship between design smells and role stereotypes. This pa- per presents a fine-grained dataset of systematically inte- grated design smells detection and role-stereotypes classi- fication data. The dataset was created from a collection of twelve (12) real-life open-source Java projects mined from GitHub. The dataset consists of 18 design smells columns and 2,513 Java classes (rows) classified into six (6) role- stereotypes taxonomy. We also clustered the dataset into ten (10) different clusters using an unsupervised learning algo- rithm. Those clusters are useful for understanding the groups of design smells that often co-occur in a particular role- stereotype category. The dataset is significant for understand- ing the non-innate relationship between design smells and role-stereotypes.enSoftware designRole-stereotypeDesign smellsSoftware qualityArticle