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Article
Publication date: 20 November 2009

Sidi Mohamed Benslimane, Mimoun Malki and Djelloul Bouchiha

Web applications are subject to continuous changes and rapid evolution triggered by increasing competition, especially in commercial domains such as electronic commerce…

Abstract

Purpose

Web applications are subject to continuous changes and rapid evolution triggered by increasing competition, especially in commercial domains such as electronic commerce. Unfortunately, usually they are implemented without producing any useful documentation for subsequent maintenance and evolution. Thereof, the maintenance of such systems becomes a challenging problem as the complexity of the web application grows. Reverse engineering has been heralded as one of the most promising technologies to support effective web application maintenance. This paper aims to present a reverse engineering approach that helps understanding existing undocumented web applications to be maintained or evolved.

Design/methodology/approach

The proposed approach provides reverse engineering rules to generate a conceptual schema from a given domain ontology by using a set of transformation rules. The reverse engineering process consists of four phases: extracting useful information; identifying a set of ontological constructs representing the concepts of interest; enriching the identified set by additional constructs; and finally deriving a conceptual schema.

Findings

The advantage of using ontology for conceptual data modeling is the reusability of domain knowledge. As a result, the conceptual data model will be made faster, easier and with fewer errors than creating it in usual way. Designers can use the extracted conceptual schema to gain a better understanding of web applications and to assist in their maintenance.

Originality/value

The strong point of this approach is that it relies on a very rich semantic reference that is domain ontology. However, it is not possible to make a straightforward transformation of all elements from a domain ontology into a conceptual data model because ontology is semantically richer than data conceptual models.

Details

International Journal of Web Information Systems, vol. 5 no. 4
Type: Research Article
ISSN: 1744-0084

Keywords

Content available
Article
Publication date: 20 November 2009

Ismail Khalil

460

Abstract

Details

International Journal of Web Information Systems, vol. 5 no. 4
Type: Research Article
ISSN: 1744-0084

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