Behavioral Diversity and a Probabilistically Optimal GP Ensemble
Genetic Programming and Evolvable Machines
Environmental robustness in multi-agent teams
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolution of team composition in multi-agent systems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Survey: A survey on search-based software design
Computer Science Review
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
Co-evolutionary automatic programming for software development
Information Sciences: an International Journal
| Hi-index | 0.00 |
Software fault tolerance schemes often employ multiple software versions developed to meet the same specification. If the versions fail independently of each other, they can be combined to give high levels of reliability. While design diversity is a means to develop these versions, ithas been questioned because it increases development costs and because reliability gains are limited by common-mode failures. We propose the use of genetic programming to generate multiple software versions and postulate that these versions can be forced to differ by varying parameters to the genetic programming algorithm. This might prove a cost-effective approach to obtain forced diversity and make possible controlled experiments with large numbers of diverse development methodologies. This paper qualitatively compares the proposed approach to design diversity and its sources of diversity. An experiment environment to evaluate whether significant diversity can be generated is outlined.