Deep learning (DL) defines a new data-driven programming paradigm where the internal
system logic is largely shaped by the training data. The standard way of evaluating DL …

Mutation Testing is a fault-based software testing technique that has been widely studied for
over three decades. The literature on Mutation Testing has contributed a set of approaches …

Context The field of mutation analysis has been growing, both in the number of published
papers and the number of active researchers. This special issue provides a sampling of …

Fault localization methods seek to identify faulty program statements based on the
information provided by the failing and passing test executions. Spectrum‐based methods …

Several module and class testing techniques have been applied to object‐oriented (OO)
programs, but researchers have only recently begun developing test criteria that evaluate …

We present MUSE (MUtation-baSEd fault localization technique), a new fault localization
technique based on mutation analysis. A key idea of MUSE is to identify a faulty statement …

This paper introduces a new paradigm for Mutation Testing, which we call Higher Order
Mutation Testing (HOM Testing). Traditional Mutation Testing considers only first order …

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 …

Mutation analysis is a powerful technique for assessing and improving the quality of test
data used to unit test software. Unfortunately, current automated mutation analysis systems …

The need for test adequacy criteria is widely recognized. Several criteria have been
proposed for the assessment of adequacy of tests at the unit level. However, there remains a …