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Predicting software test effort in iterative development using a dynamic Bayesian network

It is important to manage iterative projects in a way to maximize quality and minimize cost. To achieve high quality, accurate project estimates are of high importance. It is challenging to predict the effort that is required to perform test activities in an iterative development. If testers put extra effort in testing then schedule might be delayed, however, if testers spend less effort then quality could be affected. Currently there is no model for test effort prediction in iterative development to overcome such challenges. This paper introduces and validates a dynamic Bayesian network to predict test effort in iterative software development. In this research work, the proposed framework is evaluated in a number of ways: First, the framework behavior is observed by considering different parameters and performing initial validation. Then secondly, the framework is validated by incorporating data from two industrial projects. The accuracy of the results has been verified through different prediction accuracy measurements and statistical tests. The results from the verification confirmed that the framework has the ability to predict test effort in iterative projects accurately.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-6042
Date January 2010
CreatorsAwan, Nasir Majeed, Alvi, Adnan Khadem
PublisherBlekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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