Quality modelling and metrics of Web-based information systems

Abstract

In recent years, the World Wide Web has become a major platform for software applications. Web-based information systems have been involved in many areas of our everyday life, such as education, entertainment, business, manufacturing, communication, etc. As web-based systems are usually distributed, multimedia, interactive and cooperative, and their production processes usually follow ad-hoc approaches, the quality of web-based systems has become a major concern. Existing quality models and metrics do not fully satisfy the needs of quality management of Web-based systems. This study has applied and adapted software quality engineering methods and principles to address the following issues, a quality modeling method for derivation of quality models of Web-based information systems; and the development, implementation and validation of quality metrics of key quality attributes of Web-based information systems, which include navigability and timeliness. The quality modeling method proposed in this study has the following strengths. It is more objective and rigorous than existing approaches. The quality analysis can be conducted in the early stage of system life cycle on the design. It is easy to use and can provide insight into the improvement of the design of systems. Results of case studies demonstrated that the quality modeling method is applicable and practical. Practitioners can use the modeling method to develop their own quality models. This study is amongst the first comprehensive attempts to develop quality measurement for Web-based information systems. First, it identified the relationship between website structural complexity and navigability. Quality metrics of navigability were defined, investigated and implemented. Empirical studies were conducted to evaluate the metrics. Second, this study investigated website timeliness and attempted to find direct and indirect measures for the quality attribute. Empirical studies for validating such metrics were also conducted. This study also suggests four areas of future research that may be fruitful