利用線性權重組合模型改進軟體開發工作量預估精確度的架構

A Framework for Improving the Accuracy of Software Effort Estimation Using Linearly Weighted Combinational Models

歐比娜(Nancy Ofelia Urbina Rodas)

指導教授 ： 黃慶育

國立清華大學/電機資訊學院/資訊系統與應用研究所/碩士(2009年)

https://doi.org/10.6843/NTHU.2009.00669

摘要

Create accurate predictions of software effort has been the target of many researchers for more than thirty years. Many different methods have been created with the objective of trying to achieve this goal. Unfortunately, none of these methods developed so far have been able to prove a consistent estimation. Until now, most researches have focused on trying to find a method which the estimations of software development effort are the most accurate. However, due to the complexity and the differences between various software projects, it would be very difficult for a single method to be accurate in all the cases.
We will try to show that combining software effort estimation methods can be the solution for improving the accuracy of software effort estimation. It has been shown that using only one method to estimate effort has the advantage of simplicity, but it has the disadvantage of losing the contribution of useful information others methods can provide.
The objectives of this master thesis are to integrate several software effort estimation methods and assigning the right weights to each method. We will propose a useful approach that can assign the weights based on the outcome of a criterion used to measure the accuracy of software estimation methods. Seven public datasets and five different estimation methods are use to evaluate the accuracy of our combination models.
Experimental results have shown that the proposed combination models can be a useful method for improving the estimation accuracy.

關鍵字

software effort estimation ； linear combination ； weights assignments

參考文獻

[1] M. Agrawal, K. Chari, “Software Effort, Quality, and Cycle Time: A Study of CMM Level 5 Projects”, IEEE Transactions on Software Engineering, 33(3), March, 2007, pp. 145-156.

[2] A.J Albrecht and J.E. Gaffney Jr., “Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation”, IEEE Transactions on Software Engineering, SE-9(6), Nov. 1983, pp. 639-648.

[5] B.W. Boehm, Software Engineering Economics, Prentice Hall, 1981.

[6] B.W. Boehm and R. Ross, “Theory-W Software Project Management Principles and Examples”, IEEE Transactions on Software Engineering, 15(7), July 1989, pp. 902-916.

[8] C.J. Burgess and M. Lefley, “Can Genetic Programming Improve Software Effort Estimation? A comparative Evaluation”, World Scientific Publishing Co., 16 May 2005, pp. 95-105.