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A Comparative Evalu...
A Comparative Evaluation of Using Genetic Programming for Predicting Fault Count Data
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- Afzal, Wasif (författare)
- Mälardalens högskola,Akademin för innovation, design och teknik,Blekinge Institute of Technology,IS (Embedded Systems)
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- Torkar, Richard (författare)
- Blekinge Institute of Technology
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(creator_code:org_t)
- ISBN 9781424432189
- IEEE, 2008
- 2008
- Engelska.
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Ingår i: Proceedings - The 3rd International Conference on Software Engineering Advances, ICSEA 2008, Includes ENTISY 2008: International Workshop on Enterprise Information Systems. - : IEEE. - 9780769533728 ; , s. 407-414
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Software Engineering (hsv//eng)
Nyckelord
- Genetic programming
- fault count predictions
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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