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Effort estimation for agile software development: comparative case studies using COSMIC functional size measurement and story points

Authors:

Murat Salmanoglu,

Tuna Hacaloglu,

Onur DemirorsAuthors Info & Claims

IWSM Mensura '17: Proceedings of the 27th International Workshop on Software Measurement and 12th International Conference on Software Process and Product Measurement

Pages 41 - 49

https://doi.org/10.1145/3143434.3143450

Published: 25 October 2017 Publication History

IWSM Mensura '17: Proceedings of the 27th International Workshop on Software Measurement and 12th International Conference on Software Process and Product Measurement

Effort estimation for agile software development: comparative case studies using COSMIC functional size measurement and story points

Pages 41 - 49

Abstract
References

Abstract

Agile methodologies have gained significant popularity among software development organizations during the last decade. Although agile methodologies are regarded as minimizing formal processes, they still utilize an estimation methodology for proper management. Story point is the most common input for agile effort estimation. Story point is an arbitrary measure; it reflects experiences of project participants. On the other hand, functional size is an alternative measure used in practice as an input for effort estimation. In this research, we collect and present the outcomes of three case studies which compared the effectiveness of COSMIC-based and story point based effort estimation in agile context. On selected projects of these organizations, software functional size was measured with COSMIC functional size measurement methodology. Effort prediction models were formed by using COSMIC size and actual effort spent; and the models were tested in terms of their effectiveness. The results show controversial outcomes. For all the cases, COSMIC based estimation was more precise. Therefore, COSMIC is an appropriate measure to estimate the effort in organizations that adopt agile software development. It is also observed that COSMIC allowed for computing productivity which has less disperse distribution than the productivity computed with SP. The data is also provided to help other researchers conduct their own studies.

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Digital Library

Cited By

Kumar SSingh M(2025)Agile Development Using a Hybrid Approach for Cost Estimation of IT ProjectsComputational Intelligence in Communications and Business Analytics10.1007/978-3-031-81342-9_16(182-196)Online publication date: 12-Feb-2025
https://doi.org/10.1007/978-3-031-81342-9_16
Ersoy EBagriyanik SSozer H(2024)On the Accuracy of Effort Estimations based on COSMIC Functional Size Measurement: A Case StudyProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3695402(528-537)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3695402
Yürüm OÜnlü HDemirörs O(2024)Towards the Construction of a Software Benchmarking Dataset via Systematic Literature Review2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA64295.2024.00037(194-200)Online publication date: 28-Aug-2024
https://doi.org/10.1109/SEAA64295.2024.00037
Show More Cited By

Index Terms

Effort estimation for agile software development: comparative case studies using COSMIC functional size measurement and story points
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Software development methods
        Agile software development

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cover image ACM Other conferences

IWSM Mensura '17: Proceedings of the 27th International Workshop on Software Measurement and 12th International Conference on Software Process and Product Measurement

October 2017

273 pages

ISBN:9781450348539

DOI:10.1145/3143434

General Chairs:
Miroslaw Staron
Chalmers | University of Gothenburg
,
Wilhelm Meding
Ericsson
,
Program Chairs:
Kai Petersen
Blekinge Institute of Technology
,
Cigdem Gencel
Free University of Bozen-Bolzano

Copyright © 2017 ACM.

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SWC: Software Center, University of Gothenburg, Sweden

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Published: 25 October 2017

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IWSM/Mensura '17: 27th International Workshop on Software Measurement and 12th International Conference on Software Process and Product Measurement

October 25 - 27, 2017

Gothenburg, Sweden

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Cited By

Kumar SSingh M(2025)Agile Development Using a Hybrid Approach for Cost Estimation of IT ProjectsComputational Intelligence in Communications and Business Analytics10.1007/978-3-031-81342-9_16(182-196)Online publication date: 12-Feb-2025
https://doi.org/10.1007/978-3-031-81342-9_16
Ersoy EBagriyanik SSozer H(2024)On the Accuracy of Effort Estimations based on COSMIC Functional Size Measurement: A Case StudyProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3695402(528-537)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3695402
Yürüm OÜnlü HDemirörs O(2024)Towards the Construction of a Software Benchmarking Dataset via Systematic Literature Review2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA64295.2024.00037(194-200)Online publication date: 28-Aug-2024
https://doi.org/10.1109/SEAA64295.2024.00037
Ünlü HTenekeci SÇiftçi COral İAtalay THacaloğlu TMusaoğlu BDemirǶrs O(2024)Predicting Software Functional Size Using Natural Language Processing: An Exploratory Case Study2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA64295.2024.00036(188-193)Online publication date: 28-Aug-2024
https://doi.org/10.1109/SEAA64295.2024.00036
Dewi RAraynawa TPrasanna FFelianasari NRahmawati RHartantc AKamilah LMazaya A(2024)Improving Software Size Estimation Using Data Complexity (Case Study: Research and Community Service Monitoring Apps)2024 11th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)10.1109/EECSI63442.2024.10776530(315-319)Online publication date: 26-Sep-2024
https://doi.org/10.1109/EECSI63442.2024.10776530
Dewi RSoegiarto WFernando KReihan GPuspita MAl Ghazali MRaissa SKhodijah Nurhayati C(2024)Software Size Measurement Using Data Complexities (Case Study: Marketing Kit Monitoring System)2024 11th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)10.1109/EECSI63442.2024.10776081(331-335)Online publication date: 26-Sep-2024
https://doi.org/10.1109/EECSI63442.2024.10776081
Lavazza LLocoro AMeli R(2024)Using Machine Learning and Simplified Functional Measures to Estimate Software Development EffortIEEE Access10.1109/ACCESS.2024.347142812(142505-142523)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3471428
Ünlü HKennouche DSoylu GDemirörs O(2024)Microservice-based projects in agile worldInformation and Software Technology10.1016/j.infsof.2023.107334165:COnline publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1016/j.infsof.2023.107334
Benala TKaushik ADehuri SJain L(2024)Computational intelligence for estimating software development effort: a systematic mapping studyIran Journal of Computer Science10.1007/s42044-024-00178-97:3(607-630)Online publication date: 9-Apr-2024
https://doi.org/10.1007/s42044-024-00178-9
Rankovic NRanković DIvanovic MLazić LRankovic NRanković DIvanovic MLazić L(2024)Optimizing Effort and Cost Estimation: Model Implementation Using Artificial Neural Networks and Taguchi’s Orthogonal Vector PlansRecent Advances in Artificial Intelligence in Cost Estimation in Project Management10.1007/978-3-031-76572-8_9(291-417)Online publication date: 7-Dec-2024
https://doi.org/10.1007/978-3-031-76572-8_9
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