Historically, researchers have proposed and applied many techniques to reduce the cost of
mutation testing. It has become difficult to find all techniques and to understand the cost …

Mutation testing realizes the idea of using artificial defects to support testing activities.
Mutation is typically used as a way to evaluate the adequacy of test suites, to guide the …

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 …

Deep learning (DL) has recently been widely applied to diverse source code processing
tasks in the software engineering (SE) community, which achieves competitive performance …

Mutation testing is widely used in research as a metric for evaluating the quality of test
suites. Mutation testing runs the test suite on generated mutants (variants of the code under …

This paper presents a novel methodology for localizing faults in code as it evolves. Our
insight is that the essence of failure-inducing edits made by the developer can be captured …

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 testing is a powerful methodology for evaluating the quality of a test suite. However,
the methodology is also very costly, as the test suite may have to be executed for each …

This paper reports on results from a systematic review that characterizes the state-of-the-art
on cost reduction for mutation testing. It analyzes the evolution of research on this topic and …

Mutation analysis has many applications, such as asserting the quality of test suites and
localizing faults. One important bottleneck of mutation analysis is scalability. The latest work …