A critique of software defect prediction models

Fenton, Norman; Neil, Martin

doi:10.1109/32.815326

Cited by 839 publications

(507 citation statements)

References 37 publications

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“…However, for the third phase Model Usages (see Table 3), we found only two studies providing appropriate results of the two involved steps. This finding confirms the critique from Norman and Fenton [2] that most of the existing studies on defect prediction do not provide empirical proof whether the model can be generalized for different observations.…”

Section: Explicit Research Hypothesessupporting

confidence: 80%

“…Fenton and Neil [2] remind that "Project managers make decisions about software quality using best guesses; it seems to us that will always be the case and the best that researchers can do is 1) recognize this fact and 2) improve the 'guessing' process. We, therefore, need to model the subjectivity and uncertainty that is pervasive in software development."…”

Section: Requirements For Defect Prediction a Software Projectmentioning

confidence: 99%

“…A major concern from a practitioner's point of view is that many studies reported a trained defect prediction model which show a good performance by means of cross validation with historical data [2]. Only limited studies reported the robustness of the model with different observations.…”

Section: Phase C -Model Usagesmentioning

confidence: 99%

See 2 more Smart Citations

A Framework for Defect Prediction in Specific Software Project Contexts

Wahyudin

Ramler

Biffl

2011

Software Engineering Techniques

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Abstract. Software defect prediction has drawn the attention of many researchers in empirical software engineering and software maintenance due to its importance in providing quality estimates and to identify the needs for improvement from project management perspective. However, most defect prediction studies seem valid primarily in a particular context and little concern is given on how to find out which prediction model is well suited for a given project context. In this paper we present a framework for conducting software defect prediction as aid for the project manager in the context of a particular project or organization. The framework has been aligned with practitioners' requirements and is supported by our findings from a systematical literature review on software defect prediction. We provide a guide to the body of existing studies on defect prediction by mapping the results of the systematic literature review to the framework.

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Section: Explicit Research Hypothesessupporting

confidence: 80%

Section: Requirements For Defect Prediction a Software Projectmentioning

confidence: 99%

See 1 more Smart Citation

A Framework for Defect Prediction in Specific Software Project Contexts

Wahyudin

Ramler

Biffl

2011

Software Engineering Techniques

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“…One may also seek relationships with other process and product measures such as the size of or the number of fixes in previous releases, subsystem or module size, testing effort and so on. When abundant metric data is available, and the process is sufficiently mature, models such as Bayesian nets may be useful to predict defect rates [Fenton and Neil 1999]. The above examples all relate to defect related aspects of quality.…”

Section: Seventh Law: Declining Qualitymentioning

confidence: 99%

Rules and Tools for Software Evolution Planning and Management

Lehman

Fernáandez‐Ramil

2006

Software Evolution and Feedback

110

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Abstract. When first formulated in the early seventies, the laws of software evolution were, for a number of reasons, not widely accepted as relevant to software engineering practice. Over the years, however, they have gradually become recognised as providing useful inputs to understanding of the software process. Now eight in number, they have been supplemented by the software uncertainty principle and the FEAST (Feedback, Evolution And Software Technology) hypothesis. Based on all these and on the further results of the FEAST research projects this paper develops and presents some fifty rules for application in software system process planning and management and indicates tools available or that could usefully be developed to support their application. The listing is structured according to the laws that encapsulate the observed phenomena and that lead to the recommendations. Each sublist is preceded by a textual discussion providing at least some of the reasoning that has led to the recommended procedures. The references direct the interested reader to the literature that records observed behaviours, interpretations, models and metrics obtained from industrially evolved systems, and from which the recommendations were derived.

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“…Both are solely security oriented approaches for security assessment (and not prediction) with limited traceability to the system design and quality notions. [7] argues that traditional statistical approaches are inadequate and recommends holistic models for software defect prediction, using Bayesian Networks. However, a drawback that statistical and BBN-based models suffer, is poor scalability.…”

Section: Application Of Prediction Modelsmentioning

confidence: 99%

Idea: A Feasibility Study in Model Based Prediction of Impact of Changes on System Quality

Omerovic

Andresen

Grindheim

et al. 2010

Lecture Notes in Computer Science

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Abstract. We propose a method, called PREDIQT, for model based prediction of impact of architecture design changes on system quality. PREDIQT supports simultaneous analysis of several quality attributes and their trade-offs. This paper argues for the feasibility of the PREDIQT method based on a comprehensive industrial case study targeting a system for managing validation of electronic certificates and signatures worldwide. We give an overview of the PREDIQT method, and present an evaluation of the method in terms of a feasibility study.

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A critique of software defect prediction models

Cited by 839 publications

References 37 publications

A Framework for Defect Prediction in Specific Software Project Contexts

A Framework for Defect Prediction in Specific Software Project Contexts

Rules and Tools for Software Evolution Planning and Management

Idea: A Feasibility Study in Model Based Prediction of Impact of Changes on System Quality

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