Spectrum-based fault localization (SBFL) works well for single-fault programs
but its accuracy decays for increasing fault numbers. We present FLITSR (Fault
Localization by Iterative Test Suite Reduction), a novel SBFL extension that
improves the localization of a given base metric specifically in the presence
of multiple faults. FLITSR iteratively selects reduced versions of the test
suite that better localize the individual faults in the system. This allows it
to identify and re-rank faults ranked too low by the base metric because they
were masked by other program elements.

We evaluated FLITSR over method-level spectra from an existing large synthetic
dataset comprising 75000 variants of 15 open-source projects with up to 32
injected faults, as well as method- and statement-level spectra from a new
dataset with 326 true multi-fault versions from the Defects4J benchmark set
containing up to 14 real faults. For all three spectrum types we consistently
see substantial reductions of the average wasted efforts at different fault
levels, of 30%-90% over the best base metric, and generally similarly large
increases in precision and recall, albeit with larger variance across the
underlying projects. For the method-level real faults, FLITSR also
substantially outperforms GRACE, a state-of-the-art learning-based fault
localizer.