Computing similarity in a reuse library system: an AI-based approach
ACM Transactions on Software Engineering and Methodology (TOSEM)
Improving Speed and Productivity of Software Development: A Global Survey of Software Developers
IEEE Transactions on Software Engineering
A connectionist approach for similarity assessment in case-based reasoning systems
Decision Support Systems
A case-based approach using inductive indexing for corporate bond rating
Decision Support Systems - Decision-making and E-commerce systems
Knowledge-Based Approaches for Scheduling Problems: A Survey
IEEE Transactions on Knowledge and Data Engineering
A case-based reasoning framework for workflow model management
Data & Knowledge Engineering - Special issue: Advances in business process management
Knowledge Support in Software Process Tailoring
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 3 - Volume 03
Classifying Software for Reusability
IEEE Software
A study of the non-linear adjustment for analogy based software cost estimation
Empirical Software Engineering
| Hi-index | 12.05 |
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.