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A comparative evaluation of using genetic programming for predicting fault count data
Mälardalen University, School of Innovation, Design and Engineering. Blekinge Institute of Technology. (IS (Embedded Systems))ORCID iD: 0000-0003-0611-2655
Blekinge Institute of Technology.
2008 (English)In: Proceedings - The 3rd International Conference on Software Engineering Advances, ICSEA 2008, Includes ENTISY 2008: International Workshop on Enterprise Information Systems, 2008, p. 407-414Conference paper, Published paper (Refereed)
Abstract [en]

There have been a number of software reliability growth models (SRGMs) proposed in literature. Due to several reasons, such as violation of models’ assumptions and complexity of models, the practitioners face difficulties in knowing which models to apply in practice. This paper presents a comparative evaluation of traditional models and use of genetic programming (GP) for modeling software reliability growth based on weekly fault count data of three different industrial projects. The motivation of using a GP approach is its ability to evolve a model based entirely on prior data without the need of making underlying assumptions. The results show the strengths of using GP for predicting fault count data.

Place, publisher, year, edition, pages
2008. p. 407-414
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-22272DOI: 10.1109/ICSEA.2008.9Scopus ID: 2-s2.0-57649227726ISBN: 9780769533728 (print)OAI: oai:DiVA.org:mdh-22272DiVA, id: diva2:661363
Conference
3rd International Conference on Software Engineering Advances, ICSEA 2008; Sliema; Malta; 26 October 2008 through 31 October 2008
Projects
Project_ExternalAvailable from: 2013-11-03 Created: 2013-10-31 Last updated: 2013-12-03Bibliographically approved

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Afzal, Wasif

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf