The conference on grand challenges, held in Newcastle on 30 and 31 March 2004, occurred at a particularly opportune time. The strand on the educational aspects was particularly relevant and the idea innovative in the sense that this was the first occasion on which a grand challenge event with a focus on educational issues in computing had taken place. This paper provides some of the background and includes a distillation of the educational challenges that emerged from that event.

The way in which universities moved from an elite system of education in the 1960s to a more inclusive system of education in the 1990s has been a great success story. Computer Science has played its part, becoming a subject taught in some form in almost every university in the developed world. Those of us who were in the subject at the start of its significant growth remember the battles to get Computer Science recognised as an acceptable academic subject, and the ways in which it subsequently came to dominate many of the more traditional subjects in a university's portfolio. But as we move into the 21st century universities are entering the most volatile and turbulent time for higher education since the early 1980s, and the dangers for Computer Science are acute.For the first time in its history Computer Science is not expanding; other disciplines are encroaching on its territory; the science base (at least in English schools) is in decline; the computing industry is tentative. We are now seeing 18-year-old students with at least 10 years computing experience, who can write flawless code while holding a dozen simultaneous e-conversations and watching the TV. In their highly parallel universe, they find "hello world" uninteresting (even if it has a browser interface). They are natural collaborators - wired, extrovert and hyper-social; they are digital natives whereas their teachers are digital immigrants.How will Computer Science survive the current turmoil? What can the past tell us about the future?

This paper presents a technique for automatically generating test-data to test exceptions. The approach is based on the application of a dynamic global optimization based search for the required test-data. The authors' work has focused on test-data generation for safety-critical systems. Such systems must be free from anomalous and uncontrolled behaviour. Typically, it is easier to prove the absence of any exceptions than proving that the exception handling is safe. A process for integrating automated testing with exception freeness proofs is presented as a way forward for tackling the special needs of safety critical systems. The results of a number of simple case-studies are presented and show the technique to be effective. The major result shows the application of the technique to a commercial aircraft engine controller system as part of a proof of exception freeness. This illustrates how automated testing can be effectively integrated into a formal safety-critical process to reduce costs and add value. Copyright © 2000 John Wiley & Sons, Ltd.

One of the major costs in a software project is the construction of test-data. This paper outlines a generalised test-case data generation framework based on optimisation techniques. The framework can incorporate a number of testing criteria, for both functional and non-functional properties. Application of the optimisation framework to testing specification failures and exception conditions is illustrated. The results of a number of small case studies are presented and show the efficiency and effectiveness of this dynamic optimisation-base approach to generating test-data.

Structural testing criteria are mandated in many software development standards and guidelines. The process of generating test data to achieve 100% coverage of a given structural coverage metric is labour-intensive and expensive. This paper presents an approach to automate the generation of such test data. The test-data generation is based on the application of a dynamic optimisation-based search for the required test data. The same approach can be generalised to solve other test-data generation problems. Three such applications are discussed-boundary value analysis, assertion/run-time exception testing, and component re-use testing. A prototype tool-set has been developed to facilitate the automatic generation of test data for these structural testing problems. The results of preliminary experiments using this technique and the prototype tool-set are presented and show the efficiency and effectiveness of this approach.