Comprehending Web Applications by a Clustering Based Approach

ABSTRACT

The number and the complexity of web applications are increasing dramatically to satisfy the market requests, and the need of effective approaches for comprehending them is growing accordingly. Recently, some reverse engineering methods and tools have been proposed to support the comprehension of a web application; the information recovered by these tools is usually rendered in graphical representations. However, the graphical representations become progressively less useful with large-scale applications, and do not support adequately the comprehension of the application.In this paper, to overcome this limitation, we propose an approach based on a clustering method for decomposing a web application (WA) into groups of functionally related components. The approach is based on the definition of a coupling measure between interconnected components of the WA that takes into account both the typology and the topology of the connections. The coupling measure is exploited by a clustering algorithm that produces a hierarchy of clustering. This hierarchy allows a structured approach for the comprehension of the web application to be carried out. The approach has been experimented with medium sized web applications and produced interesting and encouraging results.

Index Terms

• Computing methodologies

  • Machine learning

    • Learning paradigms

      • Unsupervised learning

        • Cluster analysis

• Information systems

  • Information retrieval