  Factors within a large-scale software system that simultaneously interact and
strongly impact the system's response under a configuration are often difficult
to identify. Although screening such a system for the existence of such
interactions is important, determining their location is more useful for system
engineers. Combinatorial interaction testing (CIT) concerns creation of test
suites that nonadaptively either detect or locate the desired interactions,
each of at most a specified size or show that no such set exists. Under the
assumption that there are at most a given number of such interactions causing
such a response, locating arrays (LAs) guarantee unique location for every such
set of interactions and an algorithm to deal with outliers and nondeterministic
behavior from real systems, we additionally require the LAs to have a
"separation" between these collections. State-of-the-art approaches generate
LAs that can locate at most one interaction of size at most three, due to the
massive number of interaction combinations for larger parameters if no
constraints are given. This paper presents LocAG, a two-stage algorithm that
generates (unconstrained) LAs using a simple, but powerful partitioning
strategy of these combinations. In particular, we are able to generate LAs with
more factors, with any desired separation, and greater interaction size than
existing approaches.
