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Continuously Improving Effort Estimation

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Software Project Effort Estimation

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Abstract

Mistaken is he who hopes that a new effort estimation will work right from the outset. Effort estimation, as with any other technology, needs to be introduced gradually into an organization and requires continuous improvement. A “Big Bang” approach to deploying new technology typically ends up with a big disappointment. Changing multiple internal processes at once usually hits upon great resistance from people who are not willing to change their behavior. Mistaken is also he who hopes that a new effort estimation, once successfully introduced, will work forever. As the context of estimation changes, its performance must be monitored, and it needs to be amended to changing conditions.

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References

  • Basili VR (1985) Quantitative evaluation of software methodology. In: Proceedings of the 1st pan pacific computer conference, vol 1, Melbourne, Australia, 10–13 Sept 1985, pp 379–398

    Google Scholar 

  • Abran A, Moore JW, Bourque P, Dupuis R (2004) Guide to the software engineering body of knowledge - 2004 Version. IEEE Computer Society Press, Los Alamitos, CA

    Google Scholar 

  • Basili VR (1993) The experience factory and its relationship to other improvement paradigms. In: Proceedings of the 4th European software engineering conference on software engineering, Garmisch-Partenkirchen, Germany, 13–17 September, pp 68–83

    Google Scholar 

  • Basili VR, Caldiera G, Rombach HD (1994a) The experience factory. In: Marciniak JJ (ed) Encyclopedia of software engineering, vol 1, 2nd edn. Wiley, Chichester, pp 469–476

    Google Scholar 

  • Basili VR, Caldiera G, Rombach HD (1994b) The goal question metric approach. In: Marciniak JJ (ed) Encyclopedia of software engineering, vol 1, 2nd edn. Wiley, New York, pp 528–532

    Google Scholar 

  • Basili VR, Lindvall M, Regardie M, Seaman C, Heidrich J, Münch J, Rombach D, Trendowicz A (2010) Linking software development and business strategy through measurement. IEEE Comput 43(4):57–65

    Article  Google Scholar 

  • Basili VR, Trendowicz A, Kowalczyk M, Heidrich J, Seaman C, Münch J, Rombach D (2014) Aligning organizations through measurement. The GQM+Strategies approach, The Fraunhofer IESE series on software and systems engineering. Springer, Heidelberg

    Google Scholar 

  • Boehm BW, Abts C, Brown AW, Chulani S, Clark BK, Horowitz E, Madachy R, Reifer D, Steece B (2000) Software cost estimation with COCOMO II. Prentice Hall, Upper Saddle River, NJ

    Google Scholar 

  • Brindgeland DM, Zahavi R (2008) Business modeling: a practical guide to realizing business value. Morgan Kaufmann, San Francisco, CA

    Google Scholar 

  • CMMI Product Team (2010) CMMI for development, Version 1.3. Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA, Technical Report CMU/SEI-2010-TR-033

    Google Scholar 

  • Covey SR (2004) The 7 habits of highly effective people. Free Press, New York

    Google Scholar 

  • Humphrey WS (1999) Managing the software process. Addison-Wesley, Reading, MA

    Google Scholar 

  • ISBSG (2009) Estimating, benchmarking research suite release 10. International Software Benchmarking Standards Group, Hawthorn, VIC

    Google Scholar 

  • Lum K, Hihn J, Menzies T (2006) Studies in software cost model behavior: do we really understand cost model performance? In: Presented at the 28th conference of the international society of parametric analysts, 23–26 May, Seattle, WA

    Google Scholar 

  • Office of Government Commerce OGC (2009) Managing successful projects with PRINCE2 2009 Edition Manual. The Stationary Office

    Google Scholar 

  • Pedler M, Burgoyne J, Boydell T (1998) The learning company: a strategy for sustainable development, 2nd edn. McGraw-Hill, London

    Google Scholar 

  • PMI (2011) Practice standard for earned value management, 2nd edn. Project Management Institute, Newtown Square, PA

    Google Scholar 

  • PMI (2013) A guide to the project management body of knowledge (PMBOK Guide), 5th edn. Project Management Institute, Newtown Square, PA

    Google Scholar 

  • Shewhart WA (1939) Statistical method from the viewpoint of quality control. Dover, New York

    Google Scholar 

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Author information

Authors and Affiliations

  1. Fraunhofer Institute for Experimental Software Engineering, Kaiserslautern, Germany

    Adam Trendowicz

  2. The University of New South Wales, Sydney, New South Wales, Australia

    Ross Jeffery

Authors
  1. Adam Trendowicz
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  2. Ross Jeffery
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Further Reading

Further Reading

  • V. Basili, A. Trendowicz, M. Kowalczyk, J. Heidrich, C. Seaman, J. Münch, and D. Rombach (2014), Aligning Organizations through Measurement. The GQM + Strategies Approach. The Fraunhofer IESE Series on Software and Systems Engineering. Springer Verlag.

    This book presents the GQM+Strategies approach for aligning organizational goals and strategies through measurement. In particular, the book specifies methodological concepts (goals, strategies, context, assumptions, measurements, interpretations) and the steps for developing their hierarchy. It also provides examples of its application based upon experience with various organizations.

  • D. Pyle (1999), Data Preparation for Data Mining. Morgan Kaufmann.

    This book synthesizes best practices in the area of data preparation and exploration. Author provides background knowledge needed for recognizing and eliminating the source of problems with data. With respect to data preparation, the book presents comprehensive information on the purposes, overall process, and common techniques of data cleansing.

  • N. Yau (2011), Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, Wiley & Sons.

    This book introduces various means of data visualization to support basic data analysis purposes such as visualizing patterns, trends over time, proportions, and relationships. Author explains how to design visualization and select the best visualization means in order to make the data tell its full story. Moreover, the author provides a brief introduction to preparing the data for analysis and visualization. Author illustrates proposed visualization means with many full-color figures.

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Trendowicz, A., Jeffery, R. (2014). Continuously Improving Effort Estimation. In: Software Project Effort Estimation. Springer, Cham. https://doi.org/10.1007/978-3-319-03629-8_16

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  • DOI: https://doi.org/10.1007/978-3-319-03629-8_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03628-1

  • Online ISBN: 978-3-319-03629-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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