Least modification principle for case-based reasoning: a software project planning experience

A software project plan is composed of stages of activities and detailed tasks to be performed, and precedence restrictions among them. A project network is very complex and its construction requires a vast amount of field knowledge and experience. To assist the construction of a software project ne...

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Bibliographic Details
Main Authors: LEE, Jae Kyu, LEE, Nobok
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2006
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/1183
http://dx.doi.org/10.1016/j.eswa.2005.06.021
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Institution: Singapore Management University
Language: English
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Summary:A software project plan is composed of stages of activities and detailed tasks to be performed, and precedence restrictions among them. A project network is very complex and its construction requires a vast amount of field knowledge and experience. To assist the construction of a software project network, we adopt the case-based reasoning approach. However, the software project network may be designed differently depending upon the adopted development methodology and the style of the manager, so full automation of adjusting a past case is almost impossible. Thus, reducing the modification effort to a minimum is very important for enhancing the project planner's performance. In this research, we develop the framework of the Least Modification Principle (LMP) for Case-based Reasoning to solve this kind of problem. LMP is applicable when a reliable estimation of modification effort is possible. To apply the LMP for project network planning, we have selected 17 factors and the values for each factor to specify software projects. The modification effort is estimated based on the syntactic structure of modification rules. The performance of LMP is demonstrated with each of 31 test cases based on the other 30 past cases. We found that the LMP approach can significantly outperform the Ordinary Factor Matching approach.