A program transformation step prediction based reengineering approach

The essence of software reengineering is to improve or transform existing software so that it can be understood, controlled and used anew. Program transformation is used as a core technique for fulfilling the various needs in the context of software reengineering. The improvement of the automation and efficiency of program transformations for reengineering is a concern in both research and industrial areas. The proposed research aims to achieve the goal by providing an appropriate mechanism to predict the transformation steps to fulfil specific reengineering targets to enhance the efficiency and correctness of reengineering through program transformations. In this thesis, a Target Driven Program Transformation Step Prediction approach (TDPTSP) is proposed to assist the process of transformation in software reengineering. The proposed approach is explored by using a transformation-intensive language Wide Spectrum Language (WSL) as an intermediate language and its toolset that provides a well-developed transformation bank containing a large number of proven transformations. The predication of transformations is an intelligent means to guide the transformation process towards reengineering targets. In order to make the identified targets tangible, the concept of Target Model (TM) is introduced for the target representation and evaluation. In the model, software metrics selected from a reengineering intensive metrics catalogue are correlated to the corresponding targets. With the quantitative measurement and the tangible target representation, the program transformation step prediction algorithm is constructed as a heuristic based search approach. Expertise for applying program transformations in the practical work is essential for the prediction operation. The prediction approach incorporates the expertise rules in addition to the metrics based approach. When predicting the transformations on domain specific applications, domain features are the vital factors. Therefore, the

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