Abstract
An Artificial Immune System Approach to Automated Program Verification: Towards a Theory of Undecidability in Biological Computing
Highlights
The biological immune system has proved to be a rich source of inspiration for computing [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]
We propose an immune system inspired Artificial Immune System algorithm for the purposes of automated program verification
We have proposed a computational framework for an immune system inspired approach for automated program verification
Summary
The biological immune system has proved to be a rich source of inspiration for computing [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]. The effectiveness of the immune response to secondary encounters is enhanced by the presence of memory cells associated with the first infection, capable of producing high- affinity Ab’s after repeat encounters. Finding the precise shape of the loop invariant is generally a non-trivial process and the algorithm proposed aims to use ‘cues’ from the program to make informed predictions about the invariant shape and help in automated program verification. The AIS will be presented with an antigen (program fragment), and the immune system cells will either produce the antibody (invariant) immediately if it has encountered this antigen before, or willundergo mutations to generate the correct antibody (invariant). The individual invariants for each program fragment will be recombined to generate the invariant for the whole program
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