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      Predicting Short-Term Defect Inflow in Large Software Projects – An Initial Evaluation

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      11th International Conference on Evaluation and Assessment in Software Engineering (EASE) (EASE)

      Evaluation and Assessment in Software Engineering (EASE)

      2-3 April 2007

      Prediction models, defect inflow, project status monitoring

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            Abstract

            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.

            Content

            Author and article information

            Contributors
            Conference
            April 2007
            April 2007
            : 1-10
            Affiliations
            [0001]IT University of Göteborg

            Gothenburg, Sweden
            [0002]Ericsson SW Research

            Ericsson AB

            Gothenburg, Sweden
            Article
            10.14236/ewic/EASE2007.4
            a3e965e8-5f71-4874-a343-cd56b67d3003
            © Miroslaw Staron et al. Published by BCS Learning and Development Ltd. 11th International Conference on Evaluation and Assessment in Software Engineering (EASE), Keele University, UK

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            11th International Conference on Evaluation and Assessment in Software Engineering (EASE)
            EASE
            11
            Keele University, UK
            2-3 April 2007
            Electronic Workshops in Computing (eWiC)
            Evaluation and Assessment in Software Engineering (EASE)
            Product
            Product Information: 1477-9358BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

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