LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

E-MDAV: A Framework for Developing Data-Intensive Web Applications

The ever-increasing adoption of innovative technologies, such as big data and cloud computing, provides significant opportunities for organizations operating in the IT domain, but also introduces considerable challenges. Such innovations… Click to show full abstract

The ever-increasing adoption of innovative technologies, such as big data and cloud computing, provides significant opportunities for organizations operating in the IT domain, but also introduces considerable challenges. Such innovations call for development processes that better align with stakeholders needs and expectations. In this respect, this paper introduces a development framework based on the OMG’s Model Driven Architecture (MDA) that aims to support the development lifecycle of data-intensive web applications. The proposed framework, named E-MDAV (Extended MDA-VIEW), defines a methodology that exploits a chain of model transformations to effectively cope with both forward- and reverse-engineering aspects. In addition, E-MDAV includes the specification of a reference architecture for driving the implementation of a tool that supports the various professional roles involved in the development and maintenance of data-intensive web applications. In order to evaluate the effectiveness of the proposed E-MDAV framework, a tool prototype has been developed. E-MDAV has then been applied to two different application scenarios and the obtained results have been compared with historical data related to the implementation of similar development projects, in order to measure and discuss the benefits of the proposed approach.

Keywords: data intensive; development; framework; intensive web; web applications

Journal Title: Informatics
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.