  Due to its importance and widespread use in industry, automated testing of
REST APIs has attracted major interest from the research community in the last
few years. However, most of the work in the literature has been focused on
black-box fuzzing. Although existing fuzzers have been used to automatically
find many faults in existing APIs, there are still several open research
challenges that hinder the achievement of better results (e.g., in terms of
code coverage and fault finding). For example, under-specified schemas are a
major issue for black-box fuzzers. Currently, EvoMaster is the only existing
tool that supports white-box fuzzing of REST APIs. In this paper, we provide a
series of novel white-box heuristics, including for example how to deal with
under-specified constrains in API schemas, as well as under-specified schemas
in SQL databases. Our novel techniques are implemented as an extension to our
open-source, search-based fuzzer EvoMaster. An empirical study on 14 APIs from
the EMB corpus, plus one industrial API, shows clear improvements of the
results in some of these APIs.
