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Of the various testing strategies, mutation testing has been empirically found to be effective in detecting faults. However, mutation often imposes unacceptable demands on computing and human resources because of the large number of mutants that need to be compiled and executed on one or more test cases. In addition, the tester needs to examine many mutants and analyze these for possible equivalence with the program under test. For these reasons, mutation is generally regarded as too expensive to use. Because one significant component of the cost of mutation is the execution of mutants against test cases, we believe that this cost can be reduced dramatically by reducing the number of mutants that need to be examined. We report results from a case study designed to investigate two alternatives for reducing the cost of mutation. The alternatives considered are randomly selected x% mutation and …