Using Fuzzy Prototypes for Software Engineering Measurement and Prediction

-The main objective of this work is to present an application of an extension of the original Knowledge Discovery in Databases (KDD) process called Fuzzy Prototypical Knowledge Discovery (FPKD) together with a FPKD based prediction model. This technique is applied to Software Engineering measurement. In order to get quality object-oriented information systems (OOIS), it is necessary to assess their quality focusing on diagrams which are available early in the development life-cycle, such as class diagrams. It is in this context where objectoriented measures are necessary to help designers evaluate internal quality characteristics of class diagrams, such as structural complexity, and based on these evaluations, predict external quality characteristics, such as maintainability which is (and will continue to be) one of the most critical OOIS quality characteristic. Hence, by means of the FPKD process we will build a prediction model for class diagram maintainability based on class diagram structural complexity metrics. Using the FPKD process we will search for fuzzy prototypes for characterising class diagrams maintainability, and later we will use these prototypes for predicting class diagram maintainability in a real case. The data used for prediction was obtained through a controlled experiment. Key-Words: Fuzzy Prototypes, Data Mining, Knowledge Discovery, Object-oriented Software Measurement, Software Quality, Complexity Metrics.