Nature-inspired Approaches in Software Faults Identification and Debugging

This paper considers software faults identification along the phases from design to testing and debugging. The following subjects are reviewed and extended: bio-inspired concepts for structuring resilient systems, genetic strategies in test data generation, Ant Colony Optimisation (ACO) algorithms for data flow analyzing and testing, artificial immune systems (AIS) based mutation testing, and fault tolerant approaches inspired by immunity principles in order to increase the software dependability. Data collected during software development cycle can be used to understand the software project evolution and its reliability.