An artificial immune system approach to automated program verification: Towards a theory of undecidability in biological computing
- Published
- Accepted
- Subject Areas
- Computational Biology, Adaptive and Self-Organizing Systems
- Keywords
- Artificial Immune System, Evolutionary Computing, Program Invariant, Automatic Program Verification, Shape of Invariant, Undecidability, Incomputability, Biological Computing, Immuno-computing
- Copyright
- © 2017 Banerjee
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 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.2690v1
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.
Author Comment
This is a preprint submission to PeerJ Preprints.