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A framework for the analysis of software cost estimation accuracy

Published: 21 September 2006 Publication History

Abstract

Many software companies track and analyze project performance by measuring cost estimation accuracy. A high estimation error is frequently interpreted as poor estimation skills. This is not necessarily a correct interpretation. High estimation error can also be a result of other factors, such as high estimation complexity and insufficient cost control of the project. Through a real-life example we illustrate how the lack of proper estimation error analysis technique can bias analyses of cost estimation accuracy and lead to wrong conclusions. Further, we examine a selection of cost estimation studies, and show that they frequently do not take the necessary actions to ensure meaningful interpretations of estimation error data. Motivated by these results, we propose a general framework that, we believe, will improve analyses of software cost estimation error.

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cover image ACM Conferences
ISESE '06: Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
September 2006
388 pages
ISBN:1595932186
DOI:10.1145/1159733
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 21 September 2006

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Author Tags

  1. analysis
  2. estimation error
  3. process improvement
  4. software cost estimation

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  • (2023)Evaluation of Probabilistic Project Cost EstimatesIEEE Transactions on Engineering Management10.1109/TEM.2021.306705070:10(3481-3496)Online publication date: Oct-2023
  • (2021)Efficiency Improvement of Function Point-Based Software Size Estimation With Deep Learning ModelIEEE Access10.1109/ACCESS.2020.29985819(107124-107136)Online publication date: 2021
  • (2019)Applying COCOMO II for a DO-178C Safety-Critical Software Effort EstimationJournal of Aerospace Technology and Management10.5028/jatm.v11.1031Online publication date: 2019
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  • (2016)Using Bayesian Networks to Obtain the Task's Parameters for Schedule Planning in Scrum2016 4th International Conference in Software Engineering Research and Innovation (CONISOFT)10.1109/CONISOFT.2016.33(167-174)Online publication date: Apr-2016
  • (2015)Tools & methods for software effort estimation using use case points model — A reviewInternational Conference on Computing, Communication & Automation10.1109/CCAA.2015.7148498(874-879)Online publication date: May-2015
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