Investigate the potential benefits of co-optimization [12,13]
Work in Progress and Future Work
Implement adaptive parameter control
Investigate options for detecting errors like false positives
Parameter sensitivity analysis
 J. P. Cartlidge. Rules of Engagement: Competitive Coevolutionary Dynamics in Computational Systems. PhD thesis, University of Leeds, 2004.
 J. R. Koza. Genetic Programming: On the Programming of Computers by the Means of Natural Selection. MIT Press, Cambridge MA, 1992.
 J. R. Koza. Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge MA, 1994.
 J. R. Koza. Genetic Programming III: Darwinian Invention and Problem Solving. Morgan Kaufmann, 1999.
 J. R. Koza. Genetic Programming IV: Routine Human-Competitive Machine Intelligence. Kluwer Acadmeic Publishers, 2003.
 F. Lammermann and S. Wappler. Benefits of software measures for evolutionary white-box testing. In Proceedings of GECCO 2005 - the Genetic and Evolutionary Computation Conference, pages 1083–1084, Washington DC, 2005. ACM, ACM Press.
 T. Mantere and J. T. Alander. Developing and testing structural light vision software by co-evolutionary genetic algorithm. In QSSE 2002 The Proceedings of the Second ASERC Workshop on Quantative and Soft Computing based Software Engineering, pages 31–37. Alberta Software Engineering Research Consortium (ASERC) and the Department of Electrical and Computer Engineering, University of Alberta, Feb. 2002
 T. Mantere and J. T. Alander. Testing digital halftoning software by generating test images and filters co-evolutionarily. In Proceedings of SPIE Vol. 5267 Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision, pages 257–258. SPIE, Oct. 2003.
 M. Newman. Software Errors Cost U.S. Economy $59.5 Billion Annually. NIST News Release, June 2002.
 C. D. Rosin and R. K. Belew. Methods for competitive coevolution: Finding opponents worth beating. In L. Eshelman, editor, Proceedings of the Sixth International Conference on Genetic Algorithms, pages 373–380, San Francisco, CA, 1995. Morgan Kaufmann.
 C. D. Rosin and R. K. Belew. New methods for competitive coevolution. Evolutionary Computation, 5(1):1–29, 1997.
 T. Service. Co-optimization: A generalization of coevolution. Master's thesis, Missouri University of Science and Technology, 2008.
 T. Service and D. Tauritz. Co-optimization algorithms. In Proceedings of GECCO 2008 - the Genetic and Evolutionary Computation Conference, pages 387-388, 2008.
 P. Tonella. Evolutionary testing of classes. In Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis, pages 119–128, Boston, Massachusetts, 2004. ACM Press.
 S. Wappler and F. Lammermann. Using evolutionary algorithms for the unit testing of object-oriented software. In Proceedings of GECCO 2005 - the Genetic and Evolutionary Computation Conference, pages 1053–1060, Washington DC, 2005. ACM, ACM Press.
 S. Wappler and J. Wegener. Evolutionary unit testing of object-oriented software using strongly-typed genetic programming. In Proceedings of GECCO 2006 - the Genetic and Evolutionary Computation Conference, pages 1925– 1932, Seattle, Washington, 2006. ACM, ACM Press.
Koza’s GP Evolutionary Model Back to future work slide