Coverage-guided greybox fuzzing has become one of the most prevalent techniques for
finding software bugs. Coverage metric, which decides how a fuzzer selects new seeds, is …

With the increasing adoption of Deep Neural Network (DNN) models as integral parts of
software systems, efficient operational testing of DNNs is much in demand to ensure these …

Machine learning may enable the automated generation of test oracles. We have
characterized emerging research in this area through a systematic literature review …

Mutation testing has been very actively investigated by researchers since the 1970s, and
remarkable advances have been achieved in its concepts, theory, technology, and empirical …

Automatic unit test generation that explores the input space and produces effective test
cases for given programs have been studied for decades. Many unit test generation tools …

Search‐based unit test generation, if effective at fault detection, can lower the cost of testing.
Such techniques rely on fitness functions to guide the search. Ultimately, such functions …

Automated test generation based on symbolic execution can be beneficial for systematically
testing safety-critical software, to facilitate test engineers to pursue the strict testing …

A fundamental challenge of software testing is the statistically well-grounded extrapolation
from program behaviors observed during testing. For instance, a security researcher who …

Test data generation is one of the key activities that has a significant impact on the efficiency
and effectiveness of software testing. Since manual test data generation is quite inefficient …

Automatic test case generation (ATCG) is the active research topic in software testing
engineering, which can greatly reduce the cost of software testing. In automated test case …