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Prediction of Overoptimistic Predictions

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10th International Conference on Evaluation and Assessment in Software Engineering (EASE) (EASE)

Evaluation and Assessment in Software Engineering (EASE)

10 - 11 April 2006

Effort prediction, optimism, ASQ, LOT-R

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      Abstract

      Overoptimistic predictions are common in software engineering projects, e.g., the average software project cost overrun is about 30%. This paper examines the use of two popular general tests of optimism (the ASQ and the LOT-R test) to select software engineers that are less likely to provide overoptimistic predictions. A necessary, but not sufficient, condition for this use is that there is a strong relationship between optimism score, as measured by the ASQ and LOT-R tests, and predictions. We report from two experiments on this topic. The experiments suggest that the relation between optimism score as measured by ASQ or LOT-R and predictions is too weak to enable a use of these optimism measurement instruments to select more realistic estimators in software organizations. Our results also suggest that a person’s general level of optimism and over-optimistic predictions of performance are, to a large extent, unrelated.

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            Author and article information

            Affiliations
            [1 ]Simula Research Laboratory, P.O. Box 134, NO-1325 Lysaker, Norway
            [2 ]Hedmark University, Rena, Norway
            Contributors
            Conference
            April 2006
            April 2006
            : 1-10
            10.14236/ewic/EASE2006.5
            © Magne Jørgensen et al. Published by BCS Learning and Development Ltd. 10th 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/

            10th International Conference on Evaluation and Assessment in Software Engineering (EASE)
            EASE
            10
            Keele University, UK
            10 - 11 April 2006
            Electronic Workshops in Computing (eWiC)
            Evaluation and Assessment in Software Engineering (EASE)
            Product
            Product Information: 1477-9358 BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

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