Conference proceeding
Predicting Change Impact from Logical Models
2009 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE, CONFERENCE PROCEEDINGS, pp 467-470
01 Jan 2009
Abstract
To improve the ability of predicting the impact scope of a given change, we present two approaches applicable to the maintenance of object-oriented software systems. Our first approach exclusively uses a logical model extracted from UML relations among classes, and our other, hybrid approach additionally considers information mined from version histories. Using the open source Hadoop system, we evaluate our approaches by comparing our impact predictions with predictions generated using existing data mining techniques, and with actual change sets obtained from hug reports. We show that both our approaches produce better predictions when the system is immature and the version history is not well-established, and our hybrid approach produces comparable results with data mining as the system evolves.
Metrics
Details
- Title
- Predicting Change Impact from Logical Models
- Creators
- Sunny Wong - Drexel UniversityYuanfang Cai - Drexel UniversityIEEE Comp Soc
- Publication Details
- 2009 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE, CONFERENCE PROCEEDINGS, pp 467-470
- Series
- Proceedings-IEEE International Conference on Software Maintenance
- Publisher
- IEEE
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000279595400060
- Scopus ID
- 2-s2.0-70849109720
- Other Identifier
- 991019167711204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Software Engineering
- Computer Science, Theory & Methods