abstract = "It is said ninety percent of faults that survive
manufacturer's testing procedures are complex. That is,
the corresponding bug fix contains multiple changes.
Higher order mutation testing is used to study defect
interactions and their impact on software testing for
fault finding. We adopt a multi-objective Pareto
optimal approach using Monte Carlo sampling, genetic
algorithms and genetic programming to search for higher
order mutants which are both hard-to-kill and
realistic. The space of complex faults (higher order
mutants) is much larger than that of traditional first
order mutations which correspond to simple faults,
nevertheless search based approaches make this
scalable. The problems of non-determinism and
efficiency are overcome. Easy to detect faults may
become harder to detect when they interact and
impossible to detect single faults may be brought to
light when code contains two such faults. We use strong
typing and BNF grammars in search based mutation
testing to find examples of both in ancient heavily
optimised every day C code.",
notes = "Extended version of \cite{langdon:2009:TAICPART}
Slides
http://www.cs.ucl.ac.uk/staff/W.Langdon/taicpart2009/langdon_27-oct-2010.pdf