  Pointer analysis is a foundational analysis leveraged by various static
analyses. Therefore, it gathered wide attention in research for decades. Some
pointer analysis frameworks are based on succinct declarative specifications.
However, these tools are heterogeneous in terms of the underlying intermediate
representation (IR), heap abstraction, and programming methodology. This
situation complicates a fair comparison of these frameworks and thus hinders
further research. Consequently, the literature lacks an evaluation of the
strengths and weaknesses of these tools.
  In this work, we evaluate two major frameworks for pointer analysis, WALA and
Doop, on the DaCapo set of benchmarks. We compare the pointer analyses
available in Wala and Doop, and conclude that---even though based on a
declarative specification---Doop provides a better pointer analysis than Wala
in terms of precision and scalability. We also compare the two IRs used in
Doop, i.e., Jimple from the Soot framework and IR from the Wala framework. Our
evaluation shows that in the majority of the benchmarks Soot's IR gives a more
precise and scalable pointer analysis. Finally, we propose a micro-benchmark
\emph{PointerBench}, for which we manually validate the points-to statistics to
evaluate the results of these tools.
