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Reducing estimation uncertainty with continuous assessment: tracking the "cone of uncertainty"

Authors:

Pongtip Aroonvatanaporn,

Chatchai Sinthop,

Barry BoehmAuthors Info & Claims

ASE '10: Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering

Pages 337 - 340

https://doi.org/10.1145/1858996.1859065

Published: 20 September 2010 Publication History

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Abstract

Accurate software cost and schedule estimations are essential especially for large software projects. However, once the required efforts have been estimated, little is done to recalibrate and reduce the uncertainty of the initial estimates. To address this problem, we have developed and used a framework to continuously monitor the software project progress and readjust the estimated effort utilizing the Constructive Cost Model II (COCOMO II) and the Unified CodeCount Tool developed by the University of Southern California (USC). As a software project progresses, we gain more information about the project itself, which can then be used to assess and re-estimate the effort required to complete the project. With more accurate estimations and less uncertainties, the quality and goal of project outcome can be assured within the available resources. The paper thus also provides and analyzes empirical data on how projects evolve within the familiar software "cone of uncertainty".

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Karanikolas CDimitroulakos GMasselos K(2022)Simulating Software Evolution to Evaluate the Reliability of Early Decision-making among Design Alternatives toward MaintainabilityACM Transactions on Software Engineering and Methodology10.1145/356993132:3(1-38)Online publication date: 31-Oct-2022
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Index Terms

Reducing estimation uncertainty with continuous assessment: tracking the "cone of uncertainty"
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Implementation management
        Pricing and resource allocation
      2. Project and people management
2. Software and its engineering
  1. Software creation and management

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Published In

ASE '10: Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering

September 2010

534 pages

ISBN:9781450301169

DOI:10.1145/1858996

General Chair:
Charles Pecheur
Université catholique de Louvain, Belgium
,
Program Chairs:
Jamie Andrews
University of Western Ontario, Canada
,
Elisabetta Di Nitto
Politecnico di Milano, Italy

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: 20 September 2010

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ASE10: IEEE/ACM International Conference on Automated Software Engineering

September 20 - 24, 2010

Antwerp, Belgium

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Overall Acceptance Rate 82 of 337 submissions, 24%

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Gogichaty MIvanov VKruglov APedrycz WSamatova ASucci GValeev R(2023)A Systemic Approach to Evaluating the Organizational Agility in Large-Scale CompaniesIEEE Access10.1109/ACCESS.2023.323442411(3307-3323)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3234424
Karanikolas CDimitroulakos GMasselos K(2022)Simulating Software Evolution to Evaluate the Reliability of Early Decision-making among Design Alternatives toward MaintainabilityACM Transactions on Software Engineering and Methodology10.1145/356993132:3(1-38)Online publication date: 31-Oct-2022
https://dl.acm.org/doi/10.1145/3569931
Li YShibata HTakama Y(2020)User Story Driven Adaptive Planning Framework in Personal Daily Context2020 International Symposium on Community-centric Systems (CcS)10.1109/CcS49175.2020.9231325(1-6)Online publication date: 23-Sep-2020
https://doi.org/10.1109/CcS49175.2020.9231325
Petrevska Nechkoska RPetrevska Nechkoska R(2019)Theoretical Foundations: Management—Information Systems—ComplexityTactical Management in Complexity10.1007/978-3-030-22804-0_3(65-134)Online publication date: 11-Aug-2019
https://doi.org/10.1007/978-3-030-22804-0_3
Wang YWang LLi YZhu X(2017)Time Distribution of Software Stage Effort2017 24th Asia-Pacific Software Engineering Conference Workshops (APSECW)10.1109/APSECW.2017.9(41-49)Online publication date: Dec-2017
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Ferrucci FGravino CSarro FWagner SDi Penta M(2014)Exploiting prior-phase effort data to estimate the effort for the subsequent phasesProceedings of the 10th International Conference on Predictive Models in Software Engineering10.1145/2639490.2639509(42-51)Online publication date: 17-Sep-2014
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Aroonvatanaporn PKoolmanojwong SBoehm BJeffery RRaffo DArmbrust OHuang L(2012)COTIPMOProceedings of the International Conference on Software and System Process10.5555/2664360.2664366(28-37)Online publication date: 2-Jun-2012
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The role of outcome feedback in improving the uncertainty assessment of software development effort estimates

The Impact of Lessons-Learned Sessions on Effort Estimation and Uncertainty Assessments

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