dc.contributor.author | Barson, P. | |
dc.contributor.author | Davey, N. | |
dc.contributor.author | Frank, R. | |
dc.contributor.author | Tansley, D. | |
dc.date.accessioned | 2010-11-04T15:51:47Z | |
dc.date.available | 2010-11-04T15:51:47Z | |
dc.date.issued | 1995 | |
dc.identifier.citation | Barson , P , Davey , N , Frank , R & Tansley , D 1995 , Dynamic competitive learning applied to the clone detection problem . UH Computer Science Technical Report , vol. 220 , University of Hertfordshire . | |
dc.identifier.other | dspace: 2299/4963 | |
dc.identifier.uri | http://hdl.handle.net/2299/4963 | |
dc.description.abstract | A novel neural network architecture, 'Dynamic Competitive Learning', has been applied to the software clone detection problem in telecommunications systems. A software clone is a copy (subsequently modified), of a piece of existing code; it is common practice in large systems to obtain similar code via reuse of fully tested code. This paper discusses a hierarchical network with dramatically reduced training time compared to a Self Organising Map, but with at least as good a classification performance. | en |
dc.format.extent | 1380441 | |
dc.language.iso | eng | |
dc.publisher | University of Hertfordshire | |
dc.relation.ispartofseries | UH Computer Science Technical Report | |
dc.title | Dynamic competitive learning applied to the clone detection problem | en |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Science & Technology Research Institute | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |