Though mutation testing has been widely studied for more than thirty years, the prevalence and properties of equivalent mutants remain largely unknown. We report on the causes and prevalence of equivalent mutants and their relationship to stubborn mutants (those that remain undetected by a high quality test suite, yet are non-equivalent). Our results, based on manual analysis of 1,230 mutants from 18 programs, reveal a highly uneven distribution of equivalence and stubbornness. For example, the ABS class and half UOI class generate many equivalent and almost no stubborn mutants, while the LCR class generates many stubborn and few equivalent mutants. We conclude that previous test effectiveness studies based on fault seeding could be skewed, while developers of mutation testing tools should prioritise those operators that we found generate disproportionately many stubborn (and few equivalent) mutants.
Yao et al. REF have reported on the causes and prevalence of equivalent mutants and their relationship to stubborn mutants based on a manual analysis of 1230 mutants.
A study of equivalent and stubborn mutation operators using human analysis of equivalence
ICSE 2014
Computer Science