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Blockchain-Based Software Effort Estimation: An Empirical Study

delete2022-01-01
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OA
AI
M
Mansoor Ahmed
N
Naeem Iqbal
F
Faraz Hussain
M
Murad-Ali Khan
M
Markus Helfert
K
Kim, Jungsuk *
I
Imran *
DOI:10.1109/ACCESS.2022.3216840delete
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摘要

摘要

En 中文
Context: The success or failure of any software development project significantly depends on the accuracy of its effort estimates. Software development effort estimation is the foundation for project bidding, budgeting, planning, and cost control. Problem: The literature shows that a lot of work has been done on software effort estimation. But still, there is a need for improvement in effort estimation by introducing new methodologies. The structured group-based and analogy-based effort estimations are the widely used estimation methods. Nevertheless, there are several shortcomings of using these methods such as lack of experts, lack of historical data, and biasness in expert opinion, which negatively affect the estimation results. Motivation: With the advancement of technologies, such limitations could be overcome. Such as leveraging the applicability of blockchain in several domains such as improvement in the software development process and network security. Method: In this article, we have proposed a Blockchain-Based Software Effort Estimation (BBSEE) methodology to improve the software effort estimation. We employ the proposed method using Web and blockchain technologies. Moreover, we also proposed evaluation criteria to assess the efficacy of the proposed method in terms of Mean Magnitude of Relative Error (MMRE), Mean Absolute Error (MAE) and percentage of successful predictions falling (PRED (25)). Result: We performed several case studies and analyses of expert opinions of 52 organizations to present the efficacy of the proposed method. Conclusion: We observe that the BBSEE method outperforms expert judgment and analogy-based effort estimation methodologies in terms of software effort estimation.
Keyword:
Software effort estimation
blockchain
blockchain-based software engineering
analogy-based estimation
group-based estimation
estimation error
software engineering

期刊

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IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

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Gachon University
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comsats university islamabad (cui)
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Jeju National University
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