On the selection of software defect estimation techniques

Estimating the number of defects in a software product is an important and challenging problem. A multitude of estimation techniques have been proposed for defect prediction. However, not all techniques are applicable in all cases. The selection of the proper approach to use depends on multiple fact...

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Bibliographic Details
Published in:Software testing, verification & reliability verification & reliability, 2011-06, Vol.21 (2), p.125-152
Main Authors: Cangussu, João W., Haider, Syed W., Cooper, Kendra, Baron, Michael
Format: Article
Language:English
Subjects:
Availability
Computer programs
defect estimation
Defects
estimation theory
Indication
Program verification (computers)
Ranking
Software
Software reliability
software testing
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Summary:Estimating the number of defects in a software product is an important and challenging problem. A multitude of estimation techniques have been proposed for defect prediction. However, not all techniques are applicable in all cases. The selection of the proper approach to use depends on multiple factors: the features of the approach; the availability of resources; and the goals for using the estimated defect data. In this paper a survey of existing estimation techniques and a decision support approach for selecting the most suitable defect estimation technique for a project, with specific goals, is proposed. The results of the ranking are a clear indication that no estimation technique provides a single, comprehensive solution; the selection must be done according to a given scenario. Copyright © 2009 John Wiley & Sons, Ltd. The paper presents a mathematical and a practical characterization of existing defect estimation techniques. A methodology based on the Analytic Hierarchy Process (AHP), a Multi‐Criteria Decision Making (MCDM) approach, is used to rank the existing techniques under different scenarios according to their specified characterization. The scenarios presented in the paper are derived from the process maturity levels defined in the Capability Maturity Model (CMM), but the approach can be used with any specified scenario. It is clear that no estimation technique provides a comprehensive solution and the ‘best’ choice depends on the given scenario. Copyright © 2009 John Wiley & Sons, Ltd.
ISSN:0960-0833
1099-1689
DOI:10.1002/stvr.419