Search engines are among the most useful and high-profile resources on the Internet. The problem of finding information on the Internet has been replaced with the problem of knowing where search engines are, what they are designed to retrieve, and how to use them. This article describes and evaluates SavvySearch, a metasearch engine designed to intelligently select and interface with multiple remote search engines. The primary metasearch issue examined is the importance of carefully selecting and ranking remote search engines for user queries. We studied the efficacy of SavvySearch's incrementally acquired metaindex approach to selecting search engines by analyzing the effect of time and experience on performance. We also compared the metaindex approach to the simpler categorical approach and showed how much experience is required to surpass the simple scheme.

During testing, it is nearly impossible to run all statements or branches of a program. It is especially difficult to test the code used to respond to exceptional conditions. This untested code, often the error recovery code, will tend to be an error prone part of a system. We show that test coverage can be increased through an "assertion violation" technique for injecting software faults during execution. Using our prototype tool, Visual C-Patrol (VCP), we were able to substantially increase test branch coverage in four software systems studied.