Genetic Algorithm Based Restructuring of Web Applications Using Web Page Relationships and Metrics

The structure of Web applications tends to deteriorate with time as they undergo maintenance. Web applications with structural flaws increase maintenance costs, decrease component reuses, and reduce software life cycle. In this paper, we describe a genetic algorithm based restructuring approach of Web applications using Web page relationships and metrics. Our approach consists of two parts. First, metrics are derived from Web application. Next, Web application is clustered using the metrics. Then the Web application is refined by software engineers.

[1]  D. E. Goldberg,et al.  Genetic Algorithms in Search, Optimization & Machine Learning , 1989 .

[2]  Emden R. Gansner,et al.  Using automatic clustering to produce high-level system organizations of source code , 1998, Proceedings. 6th International Workshop on Program Comprehension. IWPC'98 (Cat. No.98TB100242).

[3]  Giuseppe A. Di Lucca,et al.  Reverse engineering Web applications: the WARE approach , 2004, J. Softw. Maintenance Res. Pract..

[4]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[5]  Paolo Tonella,et al.  Web application transformations based on rewrite rules , 2002, Inf. Softw. Technol..

[6]  Byung Ro Moon,et al.  Genetic Algorithm and Graph Partitioning , 1996, IEEE Trans. Computers.

[7]  Giuseppe A. Di Lucca,et al.  Comprehending Web applications by a clustering based approach , 2002, Proceedings 10th International Workshop on Program Comprehension.

[8]  Sourav S. Bhowmick,et al.  A survey of Web metrics , 2002, CSUR.

[9]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[10]  Massimiliano Di Penta,et al.  Supporting Web application evolution by dynamic analysis , 2005, Eighth International Workshop on Principles of Software Evolution (IWPSE'05).