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Prediction of fault count data using genetic programming
Blekinge Institute of Technolog. (IS (Embedded Systems))ORCID iD: 0000-0003-0611-2655
Blekinge Institute of Technolog.
Blekinge Institute of Technology.
2008 (English)In: IEEE INMIC 2008: 12th IEEE International Multitopic Conference - Conference Proceedings, 2008, 349-356 p.Conference paper, Published paper (Refereed)
Abstract [en]

Software reliability growth modeling helps in deciding project release time and managing project resources. A large number of such models have been presented in the past. Due to the existence of many models, the models’ inherent complexity, and their accompanying assumptions; the selection of suitable models becomes a challenging task. This paper presents empirical results of using genetic programming (GP) for modeling software reliability growth based on weekly fault count data of three different industrial projects. The goodness of ?t (adaptability) and predictive accuracy of the evolved model is measured using ?ve different measures in an attempt to present a fair evaluation. The results show that the GP evolved model has statistically signi?cant goodness of ?t and predictive accuracy

Place, publisher, year, edition, pages
2008. 349-356 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-22275DOI: 10.1109/INMIC.2008.4777762Scopus ID: 2-s2.0-67649651866ISBN: 978424428243 (print)OAI: oai:DiVA.org:mdh-22275DiVA: diva2:661360
Conference
12th IEEE International Multitopic Conference, IEEE INMIC 2008; Karachi; Pakistan; 23 December 2008 through 24 December 2008
Projects
Project_External
Available from: 2013-11-03 Created: 2013-10-31 Last updated: 2013-12-03Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
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  • nn-NB
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Output format
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  • asciidoc
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