  Statistical fault localization is an easily deployed technique for quickly
determining candidates for faulty code locations. If a human programmer has to
search the fault beyond the top candidate locations, though, more traditional
techniques of following dependencies along dynamic slices may be better suited.
In a large study of 457 bugs (369 single faults and 88 multiple faults) in 46
open source C programs, we compare the effectiveness of statistical fault
localization against dynamic slicing. For single faults, we find that dynamic
slicing was eight percentage points more effective than the best performing
statistical debugging formula; for 66% of the bugs, dynamic slicing finds the
fault earlier than the best performing statistical debugging formula. In our
evaluation, dynamic slicing is more effective for programs with single fault,
but statistical debugging performs better on multiple faults. Best results,
however, are obtained by a hybrid approach: If programmers first examine at
most the top five most suspicious locations from statistical debugging, and
then switch to dynamic slices, on average, they will need to examine 15% (30
lines) of the code. These findings hold for 18 most effective statistical
debugging formulas and our results are independent of the number of faults
(i.e. single or multiple faults) and error type (i.e. artificial or real
errors).
