One of the goals of software engineering is the development of high quality software at a small cost an in a short period of time. In this context, several techniques have been defined for controlling the quality of software designs. Furthermore, many metrics-based mechanisms have been defined for detecting software design flaws. Most of these mechanisms and techniques focus on analyzing the source code. However, in order to reduce unnecessary rework it is important to use quality analysis techniques that allow the detection of design flaws earlier in the development cycle. We believe that these techniques should analyze design flaws starting from software models. This dissertation proposes: (i) a set of strategies to detect, in UML models, specific and recurrent design problems: Long Parameter List, God Class, Data Class, Shotgun Surgery, Misplaced Class and God Package; (ii) and the use of QMOOD quality model to analyze class diagrams. To automate the application of these mechanisms we implemented a tool: the QCDTool. The detection strategies and QMOOD model were evaluated in the context of two experimental studies. The first study analyzed the accuracy, precision and recall of the proposed detection strategies. The second study analyzed the utility of use QMOOD quality model in the class diagrams. The results of the first study have shown the benefits and drawbacks of the application in class diagrams of some of the proposed detection strategies. The second study shows that it was possible to identify, based on class diagrams, variations of the design properties and consequently, of the quality attributes in the analyzed systems.