David Cairns - Publications

COMPUTING SCIENCE AND MATHEMATICS
University \| Computing Science \| Staff \| David Cairns \| Publications	Updated 23/03/17 16:05

Dr David Cairns Publications

Home

Research

Teaching

Personal

Haraldsson, S.Ó., Woodward, J.R., Brownlee, A.E.I. & Cairns, D.E. (2017), "Exploring Fitness and Edit Distance of Mutated Python Programs", "Genetic Programming", pp 19-34, Springer.

[Abstract] [BibTeX] [DOI]

Abstract: Genetic Improvement (GI) is the process of using computational search techniques to improve existing software e.g. in terms of execution time, power consumption or correctness. As in most heuristic search algorithms, the search is guided by fitness with GI searching the space of program variants of the original software. The relationship between the program space and fitness is seldom simple and often quite difficult to analyse. This paper makes a preliminary analysis of GI’s fitness distance measure on program repair with three small Python programs. Each program undergoes incremental mutations while the change in fitness as measured by proportion of tests passed is monitored. We conclude that the fitnesses of these programs often does not change with single mutations and we also confirm the inherent discreteness of bug fixing fitness functions. Although our findings cannot be assumed to be general for other software they provide us with interesting directions for further investigation.

BibTeX:

	@inbook{Sami2017,
	  author = {Sæmundur Óskar Haraldsson and John R. Woodward and Alexander E. I. Brownlee and David E. Cairns},
	  chapter = {Exploring Fitness and Edit Distance of Mutated Python Programs},
	  publisher = {Springer},
	  year = {2017},
	  pages = {19-34},
	  doi = {http://doi.org/10.1007/978-3-319-55696-3_2}
	}

Neumann, G. & Caims, D. (2015), "A Targeted Estimation of Distribution Algorithm Compared to Traditional Methods in Feature Selection", "Computational Intelligence", November, 2015, Vol. 613, (1), pp 83-103, Madani, K., Dourado, A., Rosa, A., Filipe, J. & Kacprzyk, J. (Ed), Springer.

[Abstract] [BibTeX] [DOI] [URL]

Abstract: The Targeted Estimation of Distribution Algorithm (TEDA) introduces into an EDA/GA hybrid framework a ‘Targeting’ process, whereby the number of active genes, or ‘control points’, in a solution is driven in an optimal direction. For larger feature selection problems with over a thousand features, traditional methods such as forward and backward selection are inefficient. Traditional EAs may perform better but are slow to optimize if a problem is sufficiently noisy that most large solutions are equally ineffective and it is only when much smaller solutions are discovered that effective optimization may begin. By using targeting, TEDA is able to drive down the feature set size quickly and so speeds up this process. This approach was tested on feature selection problems with between 500 and 20,000 features using all of these approaches and it was confirmed that TEDA finds effective solutions significantly faster than the other approaches.

BibTeX:

@inbook{NeumannCompInt2015,
  author = {Neumann, G. and Caims, D.},
  chapter = {A Targeted Estimation of Distribution Algorithm Compared to Traditional Methods in Feature Selection},
  editor = {Madani, K. and Dourado, A. and Rosa, A. and Filipe, J. and Kacprzyk, J.},
  publisher = {Springer},
  year = {2015},
  volume = {613},
  number = {1},
  pages = {83-103},
  url = {http://link.springer.com/chapter/10.1007%2F978-3-319-23392-5_5},
  doi = {http://doi.org/10.1007/978-3-319-23392-5_5}
}

Neumann, G. & Cairns, D. (2013), "Applying a Hybrid Targeted Estimation of Distribution Algorithm to Feature Selection Problems", In IJCCI 2013 - Proceedings of the 5th International Joint Conference on Computational Intelligence, Vilamoura, Algarve, Portugal, 20-22 September, 2013, pp. 136-143

[BibTeX] [DOI] [URL]

BibTeX:

@inproceedings{DBLP:conf/ijcci/NeumannC13,
  author = {Geoffrey Neumann and David Cairns},
  title = {Applying a Hybrid Targeted Estimation of Distribution Algorithm to Feature Selection Problems},
  booktitle = {IJCCI 2013 - Proceedings of the 5th International Joint Conference on Computational Intelligence, Vilamoura, Algarve, Portugal, 20-22 September, 2013},
  year = {2013},
  pages = {136--143},
  url = {http://dx.doi.org/10.5220/0004553301360143},
  doi = {http://dx.doi.org/10.5220/0004553301360143}
}

Cairns, D., Fayed, M. & Mouftah, H.T. (2013), "The Prohibitive Link between Position-based Routing and Planarity", ICST Trans. Mobile Communications Applications, Vol. 3, pp e2.

[BibTeX] [DOI] [URL]

BibTeX:

@article{DBLP:journals/mca/CairnsFM13,
  author = {David Cairns and Marwan Fayed and Hussein T. Mouftah},
  journal = {ICST Trans. Mobile Communications Applications},
  year = {2013},
  volume = {3},
  pages = {e2},
  url = {http://dx.doi.org/10.4108/mca.1.3.e2},
  doi = {http://dx.doi.org/10.4108/mca.1.3.e2}
}

Neumann, G.K. & Cairns, D. (2013), "A Targeted Estimation of Distribution Algorithm Compared to Traditional Methods in Feature Selection", "Studies in Computational Intelligence (LNCS)", In Studies in Computational Intelligence, LNCS, pp In Press, Spring.