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Survey of Software Development Effort Estimation Techniques

Published: 08 February 2018 Publication History

Abstract

Software development effort estimation is one of the most crucial activities in software engineering. Effort estimation permits managers and software engineers to anticipate, forecast, and precisely quote the schedule, budget and manpower requirements. By accurately estimating the effort; software projects can be saved from under run or over run. In this paper we have summarized and then analyzed the past work of software effort estimation in a systematic way. 10 researches were surveyed and explained briefly that how they are contributing towards solving the effort estimation problem in terms of time, cost or test. It also emphasizes that various effort estimation models have different pros and cons and can be used in different context on basis of different types of historical data. The survey discovered the most popular models used for effort prediction are supervised learning algorithms. The trends identified through this survey can help in exploring the potential research areas.

References

[1]
Sabahat, N., Malik, A. A., & Azam, F. (2017). A Size Estimation Model for Board-Based Desktop Games. IEEE Access, 5, 4980-4990.
[2]
Idri, A., azzahra Amazal, F., &Abran, A. (2015). Analogy-based software development effort estimation: A systematic mapping and review. Information and Software Technology, 58, 206-230.
[3]
Wen, J., Li, S., Lin, Z., Hu, Y., & Huang, C. (2012). Systematic literature review of machine learning based software development effort estimation models. Information and Software Technology, 54(1), 41-59.
[4]
Sharma, A., &Kushwaha, D. S. (2012). Estimation of Software Development Effort from Requirements Based Complexity. Procedia Technology, 4, 716-722.
[5]
Huang, J., Li, Y. F., &Xie, M. (2015). An empirical analysis of data preprocessing for machine learning-based software cost estimation. Information and software Technology, 67, 108-127.
[6]
Nassif, A. B., Azzeh, M., Capretz, L. F., & Ho, D. (2016). Neural network models for software development effort estimation: a comparative study. NCA, 27(8), 2369-2381.
[7]
Azzeh, M., &Nassif, A. B. (2016). A hybrid model for estimating software project effort from Use Case Points. Applied Soft Computing, 49, 981-989.
[8]
Nassif, A. B., Ho, D., & Capretz, L. F. (2013). Towards an early software estimation using log-linear regression and a multilayer perceptron model. Journal of Systems and Software, 86(1), 144-160.
[9]
Dragicevic, S., Celar, S., & Turic, M. (2017). Bayesian network model for task effort estimation in agile software development. Journal of Systems and Software, 127, 109-119.
[10]
Zare, F., Zare, H. K., & Fallahnezhad, M. S. (2016). Software effort estimation based on the optimal Bayesian belief network. Applied Soft Computing, 49, 968-980.
[11]
Panda, A., Satapathy, S. M., & Rath, S. K. (2015). Empirical validation of neural network models for agile software effort estimation based on story points. Procedia Computer Science, 57, 772-781.
[12]
Gharehchopogh, F. S., Maleki, I., & Khaze, S. R. (2014). A Novel Particle Swarm Optimization Approach For Software Effort Estimation. International Journal of Academic Research, 6(2).
[13]
Rijwani, P., & Jain, S. (2016). Enhanced software effort estimation using multi layered feed forward artificial neural network technique. Procedia Computer Science, 89, 307-312.
[14]
Kocaguneli, E., Menzies, T., Bener, A., & Keung, J. W. (2012). Exploiting the essential assumptions of analogy-based effort estimation. IEEE Transactions on Software Engineering, 38(2), 425-438.
[15]
Idri, A., Hosni, M., & Abran, A. (2016). Improved estimation of software development effort using Classical and Fuzzy Analogy ensembles. Applied Soft Computing, 49, 990-1019.
[16]
Amazal, F. A., Idri, A., & Abran, A. (2014). Software development effort estimation using classical and fuzzy analogy. Int Journal of Computational Intelligence and Apps, 13(03), 1450013.
[17]
El Bajta, M. (2015, July). Analogy-based software development effort estimation in global software development. In Global Software Engineering Workshops (ICGSEW), (pp. 51-54).
[18]
Qi, F., Jing, X. Y., Zhu, X., Xie, X., Xu, B., & Ying, S. (2017). Software effort estimation based on open source projects: Case study of Github. Information and Software Technology, 92, 145-157.

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  • (2024)Agile Effort Estimation in Colombia: An Assessment and Opportunities for ImprovementScience of Computer Programming10.1016/j.scico.2024.103115(103115)Online publication date: Apr-2024
  • (2023)Software Cost and Effort Estimation: Current Approaches and Future TrendsIEEE Access10.1109/ACCESS.2023.331271611(99268-99288)Online publication date: 2023
  • (2023)Is COCOMO and Putnam relevant to e-Government? Software development efforts estimation in e-Government in the Indian state of Andhra PradeshDigital Policy, Regulation and Governance10.1108/DPRG-11-2021-014725:3(267-287)Online publication date: 23-Mar-2023
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    cover image ACM Other conferences
    ICSCA '18: Proceedings of the 2018 7th International Conference on Software and Computer Applications
    February 2018
    349 pages
    ISBN:9781450354141
    DOI:10.1145/3185089
    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: 08 February 2018

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    Author Tags

    1. Software Effort Estimation
    2. Supervised Learning
    3. Systematic literature review

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    • (2024)Agile Effort Estimation in Colombia: An Assessment and Opportunities for ImprovementScience of Computer Programming10.1016/j.scico.2024.103115(103115)Online publication date: Apr-2024
    • (2023)Software Cost and Effort Estimation: Current Approaches and Future TrendsIEEE Access10.1109/ACCESS.2023.331271611(99268-99288)Online publication date: 2023
    • (2023)Is COCOMO and Putnam relevant to e-Government? Software development efforts estimation in e-Government in the Indian state of Andhra PradeshDigital Policy, Regulation and Governance10.1108/DPRG-11-2021-014725:3(267-287)Online publication date: 23-Mar-2023
    • (2022)Method of Software Development Project Duration Estimation for Scrum Teams with Differentiated SpecializationsSystems10.3390/systems1004012310:4(123)Online publication date: 17-Aug-2022
    • (2022)Systematic Review of Machine Learning-Based Open-Source Software Maintenance Effort EstimationRecent Advances in Computer Science and Communications10.2174/266625581666622060911071216:3Online publication date: Mar-2022
    • (2022)Evolution of Software Development Effort and Cost Estimation Techniques: Five Decades Study Using Automated Text Mining ApproachMathematical Problems in Engineering10.1155/2022/57825872022(1-17)Online publication date: 2-May-2022
    • (2022)Data-driven effort estimation techniques of agile user stories: a systematic literature reviewArtificial Intelligence Review10.1007/s10462-021-10132-x55:7(5485-5516)Online publication date: 1-Oct-2022
    • (2022)Efficient Analogy-based Software Effort Estimation using ANOVA Convolutional Neural Network in Software Project ManagementSmart Intelligent Computing and Applications, Volume 110.1007/978-981-16-9669-5_35(389-400)Online publication date: 19-Apr-2022
    • (2021)Analysis of the cost factors on E-government software cost using fuzzy decision making systemJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-18963840:4(8151-8161)Online publication date: 1-Jan-2021
    • (2021)Software Testing Effort Estimation and Related ProblemsACM Computing Surveys10.1145/344269454:3(1-38)Online publication date: 17-Apr-2021
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