Software reliability measurement: prediction, estimation, and assessment
Journal of Systems and Software - Special issue on the fifth Minnowbrook workshop on software performance evaluation
Projecting Software Defects from Analyzing Ada Designs
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
Using the GQM paradigm to investigate influential factors for software process improvement
Journal of Systems and Software
A criticsm on the capture-and-recapture method for software reliability assurance
Journal of Systems and Software
A Critique of Software Defect Prediction Models
IEEE Transactions on Software Engineering
Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
Software Metrics: A Rigorous and Practical Approach
Software Metrics: A Rigorous and Practical Approach
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
Software Measurement and Estimation: A Practical Approach (Quantitative Software Engineering Series)
Software Measurement and Estimation: A Practical Approach (Quantitative Software Engineering Series)
Software development productivity on a new platform: an industrial case study
Information and Software Technology
Predicting weekly defect inflow in large software projects based on project planning and test status
Information and Software Technology
SoftCOM'09 Proceedings of the 17th international conference on Software, Telecommunications and Computer Networks
Information and Software Technology
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Predicting a defect inflow is important for project planning and monitoring purposes. For project planning purposes and for quality management purposes, an important measure is the trend of defect inflow in the project - i.e. how many defects are reported in a particular stage of the project. Predicting the defect inflow provides a mechanism of early notification whether the project is going to meet the set goals or not. In this paper we present and evaluate a method for predicting defect inflow for large software projects: a method for short-term predictions for up to three weeks in advance on a weekly basis. The contribution of this paper is the fact that our model is based on the data from project planning, status monitoring, and current trends of defect inflow and produces results applicable for large projects. The method is evaluated by comparing it to existing defect inflow prediction practices (e.g. expert estimations) at one of the large projects at Ericsson. The results show that the method provides more accurate predictions (in most cases) while decreasing the time required for constructing the predictions using current practices in the company.