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Identification and Analysis of Combined Quality Assurance Approaches

Context: Due to the increasing size and complexity of software today, the amount of effort for software quality assurance (QA) is growing and getting more and more expensive. There are many techniques lead to the improvement in software QA. Static analysis can obtain very good coverage while analyze program without execution, but it has the weakness of imprecision by false errors. In contrast, dynamic analysis can obtain only partial coverage due to a large number of possible test cases, but the reported errors are more precise. Static and dynamic analyses can complement each other by providing valuable information that would be missed by using isolated analysis technique. Although many studies investigate the QA approaches that combine static and dynamic QA techniques, it is unclear what we have learned from these studies, because no systematic synthesis exists to date. Method: This thesis is intended to provide basic key concepts for combined QA approaches. A major part of this thesis presents the systematic review that brings details discussion about state of the art on the approaches that combine static and dynamic QA techniques. The systematic review is aimed at the identification of the existed combined QA approaches, how to classify them, their purposes and input as well as introduce which combination is available. Result: The results show that, there are two relations in the combination of static and dynamic techniques such as integration and separation. Besides, the objectives of combined QA approaches were introduced according to QA process quality and product quality. The most common inputs for combined approaches were also discussed. Moreover, we identified which combination of static and dynamic techniques should or should not be used as well as the potential combination for further research.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-4007
Date January 2010
CreatorsNha, Vi Tran Ngoc
PublisherBlekinge 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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