|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
Smith, Albert V
|Title:||Genetic Improvement of Runtime and its Fitness Landscape in a Bioinformatics Application|
|Citation:||Haraldsson S, Woodward J, Brownlee A, Smith AV & Gudnason V (2017) Genetic Improvement of Runtime and its Fitness Landscape in a Bioinformatics Application In: 2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017, New York: Association for Computing Machinery, Inc. GECCO 2017: The Genetic and Evolutionary Computation Conference, 15.7.2017 - 19.7.2017, Berlin, Germany, pp. 1521-1528.|
|Conference Name:||GECCO 2017: The Genetic and Evolutionary Computation Conference|
|Conference Location:||Berlin, Germany|
|Abstract:||We present a Genetic Improvement (GI) experiment on ProbAbel, a piece of bioinformatics software for Genome Wide Association (GWA) studies. The GI framework used here has previously been successfully used on Python programs and can, with minimal adaptation, be used on source code written in other languages. We achieve improvements in execution time without the loss of accuracy in output while also exploring the vast fitness landscape that the GI framework has to search. The runtime improvements achieved on smaller data set scale up for larger data sets. Our findings are that for ProbAbel, the GI's execution time landscape is noisy but flat. We also confirm that human written code is robust with respect to small edits to the source code.|
|Status:||Book Chapter: publisher version|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|p1521-haraldsson.pdf||1.08 MB||Adobe PDF||Under Embargo until 31/12/2999 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.