UNDERSTANDING OF E-COMMERCE IS THROUGH FEATURE MODELS AND THEIR METRICS TO SUPPORT RE-MODULARIZATION

The paper addresses the e-commerce system (interpreted here as information system IS) understandability problem from the maintenance and evolution perspective. We propose a methodology that includes: (1) identification of the 3 representative systems (through clustering of a set of previously developed IS on the basis of user-oriented and temporal criteria); (2) extraction of feature models from representative systems for evaluation using similarity (measured by absolute difference value ADV) and complexity metrics leading to the definition of the reference IS RIS; (3) construction of the business logic feature model, represented as meta-graph, to reason about quality of the systems and to understand evolution trends; (4) feature model refactoring / modularization of the RIS; (5) Code-level modularization of the RIS. The methodology is supported by experiments to evaluate the analysed problems. The basic results are: (1) feature models of the representative systems; (2) metrics to evaluate complexity and similarity of the represented systems; (3) the re-engineered RIS to support better maintainability and design procedures.