Mutation testing is a powerful methodology for evaluating test suite quality. In mutation
testing, a large number of mutants are generated and executed against the test suite to …

Mutation testing offers concrete test goals (mutants) and a rigorous test efficacy criterion, but
it is expensive due to vast numbers of mutants, many of which are neither useful nor …

Mutation testing is a well-known but costly approach for determining test adequacy. The
central idea behind the approach is to generate mutants, which are small syntactic …

Mutation analysis assesses a test suite's adequacy by measuring its ability to detect small
artificial faults, systematically seeded into the tested program. Mutation analysis is …

Mutation analysis evaluates a testing technique by measur-ing how well it detects seeded
faults (mutants). Mutation analysis is hampered by inherent scalability problems—a test suite …

Various forms of selective mutation testing have long been accepted as valid
approximations to full mutation testing. This paper presents counterevidence to traditional …

This article presents the techniques and results of a novel model‐based test case
generation approach that automatically derives test cases from UML state machines. The …

Mutation testing is one of the most powerful approaches for evaluating quality of test suites.
However, mutation testing is also one of the most expensive testing approaches. This paper …

Model-based mutation analysis is a powerful but expensive testing technique. We tackle its
high computation cost by proposing an optimization technique that drastically speeds up the …

Much research on software testing and test techniques relies on experimental studies based
on mutation testing. In this paper we reveal that such studies are vulnerable to a potential …