Bioinformatics tools, and programming via chemical reaction networks (CRNs), result in simulations of a natural process such as an organism's growth, the interactions between molecules as reactions execute over time, DNA alignment, etc. CRNs themselves are representations of a naturally occurring process (a set of chemical reactions in solution), that can be provably manipulated to perform computations. While these types of abstractions form a powerful and growing computational paradigm, these are encoded as software programs, which simulate the natural processes, and hence they are prone to faults. This project develops foundations for software testing of natural representations. It is creating techniques for test generation with measurable code and model coverage and designing configuration-aware testing and optimization techniques for these systems.
|1||M. C. Gerten, A. L. Marsh, J. I. Lathrop, M. B. Cohen, A. S. Miner, T. H. Klinge, Inference and Test Generation Using Program Invariants in Chemical Reaction Networks, IEEE/ACM International Conference on Software Engineering (ICSE), May, 2022, to appear. [.pdf]|
|2.||P. Gazzillo, and M. B. Cohen, Bringing Together Configuration Research: Towards a Common Ground, In Proceedings of the ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (Onward! 2022). pp. 259–269. https://doi.org/10.1145/3563835.3568737.|
|3.||I. Mesecan, D. Blackwell, D. Clark, M.B. Cohen, J. Petke, Keeping Secrets: Multi-objective Genetic Improvement for Detecting and Reducing Information Leakage, IEEE/ACM International Conference on Automated Software Engineering (ASE), Oct. 2022, to appear. [.pdf]|
|4.||I. Mesecan, M.C. Gerten, J.I. Lathrop, M.B. Cohen, T.H. Caldas, CRNRepair: Automated Program Repair ofChemical Reaction Networks, International Workshop on Genetic Improvement @ICSE 2021, May 2021, pp. 23-30. Best paper award. [.pdf] [video]|
|5.||M.C Gerten, J.I. Lathrop, M.B. Cohen, T.H. Klinge, ChemTest: An Automated Software Testing Framework for an Emerging Paradigm, ACM/IEEE International Conference on Automated Software Engineering,
September, 2020, pp. 548–560, https://doi.org/10.1145/3324884.3416638, ACM Distinguished Paper