In recent years the use of non-traditional computing mechanisms has grown rapidly. One paradigm uses chemical reaction networks (CRNs) to compute via chemical interactions. CRNs are used to prototype molecular devices at the nanoscale such as intelligent drug therapeutics. In practice, these programs are first written and simulated in environments such as MatLab and later compiled into physical molecules such as DNA strands. However, techniques for testing the correctness of CRNs are lacking. Current methods of validating CRNs include model checking and theorem proving, but these are limited in scalability. In this paper we present the first (to the best of our knowledge) testing framework for CRNs, ChemTest. ChemTest evaluates test oracles on individual simulation traces and supports functional, metamorphic, internal and hyper test cases. It also allows for flakiness and programs that are probabilistic. We performed a large case study demonstrating that ChemTest can find seeded faults and scales beyond model checking. Of our tests, 21% are inherently flaky, suggesting that systematic support for this paradigm is needed. On average, functional tests find 66.5% of the faults, while metamorphic tests find 80.4%, showing the benefit of using metamorphic relationships in our test framework. In addition, we show how the time at evaluation impacts fault detection.

@inproceedings{paperbot5993,
  title = {ChemTest},
  author = {Michael C. Gerten and James I. Lathrop and Myra B. Cohen and Titus H. Klinge},
  booktitle = {ASE},
  year = {2020},
  doi = {10.1145/3324884.3416638}
}