This paper conducts an empirical analysis of a semiotics-based quality framework for quality assuring information models. 192 participants were trained in the concepts of the quality framework, and used it to evaluate models represented in an extended Entity Relationship (ER) language. A randomised, double-blind design was used, in which each participant independently reviewed multiple models and each model was evaluated by multiple reviewers. A combination of quantitative and qualitative analysis techniques were used to evaluate the results, including reliability analysis, validity analysis, interaction analysis, influence analysis, defect pattern analysis and task accuracy analysis.. An analysis was also conducted of the framework's likelihood of adoption in practice. The study provides strong support for the validity of the framework and suggests that it is likely to be adopted in practice, but raises questions about its reliability and the ability of participants to use it to accurately identify defects. The research findings provide clear directions for improvement of the framework. The research methodology used provides a general approach to empirical validation of quality frameworks.

The main results from a survey investigation performed in Norwegian organizations within software maintenance are presented. The results are based on responses from 52 Norwegian organizations. The amount of work being reported on maintenance in the investigation is not statistically different from what is reported in other investigations. From a functional point of view, the situation is better than previously perceived. Still, almost 45% of the work being done on information systems is not improving the information system support of the organization functionally. A large effort is used for developing replacement systems, which are needed because companies are not able to maintain the systems to keep up with organizational and technical changes.>

Traditionally performance modellers have tended to ignore the difficulty of obtaining parameter vaules which represent the resource demands of multi-layered software. In practice the use of performance engineering in large-scale systems development is limited by the cost of acquiring appropriate performance information about the various software components. However, if this information cart be reused when components are combined in different ways, then the cost of measurement can be more easily justified. Such reuse can be achieved by means of a composite work model.