An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing
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Abstract
An immune system inspired Artificial Immune System (AIS) algorithm is presented, and is used for the purposes of automated program verification. Relevant immunological concepts are discussed and the field of AIS is briefly reviewed. It is proposed to use this AIS algorithm for a specific automated program verification task: that of predicting shape of program invariants. It is shown that the algorithm correctly predicts program invariant shape for a variety of benchmarked programs. Program invariants encapsulate the computability of a particular program, e.g. whether it performs a particular function correctly and whether it terminates or not. This work also lays the foundation for applying concepts of theoretical incomputability and undecidability to biological systems like the immune system that perform robust computation to eliminate pathogens.
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2017. An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing. PeerJ Preprints 5:e2690v1 https://doi.org/10.7287/peerj.preprints.2690v1Author comment
This is a preprint submission to PeerJ Preprints.
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Competing Interests
The author declares that they have no competing interests.
Author Contributions
Soumya Banerjee conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, performed the computation work, reviewed drafts of the paper.
Data Deposition
The following information was supplied regarding data availability:
The research in this article did not generate, collect or analyse any raw data or code.
Funding
The author received no funding for this work.
