Although powerful, mutation is a computationally very expensive testing technique. In fact, its three main stages (mutant generation, mutant execution and result analysis) require many resources to be successfully accomplished. Thus, researchers have made important efforts to reduce its costs. This paper represents an additional effort in this sense. It describes the results of two experiments in which, by means of combining the original set of mutants and therefore obtaining a new set of mutants—each one with two faults—the number of mutants used is reduced to half. Results lead to believe that mutant combination does not decrease the quality of the test suite, whereas it supposes important savings in mutant execution and result analysis. Copyright © 2008 John Wiley & Sons, Ltd.

This article presents the technical and functional descriptions of a tool specifically designed for database re‐engineering. As is well known, re‐engineering is the process of (1) applying reverse engineering to a software product to obtain higher‐level specifications and (2) using these specifications as the starting point for the development of a new version of the system. Thus, the complete process can be seen as a sequence of transformation functions that operate on the different sets involved in the whole process. The starting point of the re‐engineering process is the physical schema of the database which is translated into a vendor‐independent metamodel (the logical schema) and then translated into a class diagram representing a possible conceptual schema of the database. This diagram is then taken as the starting point for the code generation process, which produces an executable application for four possible different platforms. Copyright © 2007 John Wiley & Sons, Ltd.

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Nowadays, organizations may have Web portals tailoring several websites where a wide variety of information is integrated. These portals are typically composed of a set of Web applications and services that interchange data among them. In this setting, there is no way to find out how the quality of the interchanged data is going to evolve successively. A framework is proposed for establishing trust networks based on the Data Quality (DQ) levels of the interchanged data. We shall consider two kinds of DQ: inherent DQ and pragmatic DQ. Making a decision about the selection of the most suitable data supplier will be based on the estimation of the best expected pragmatic DQ levels. In addition, an example is presented to ilustrate framework operation.