Conference proceeding
Applying spectral methods to software clustering
Ninth Working Conference on Reverse Engineering, 2002. Proceedings, v 2002-, pp 3-10
2002
Abstract
The application of spectral methods to the software clustering problem has the advantage of producing results that are within a known factor of the optimal solution. Heuristic search methods, such as those supported by the Bunch clustering tool, only guarantee local optimality which may be far from the global optimum. In this paper, we apply the spectral methods to the software clustering problem and make comparisons to Bunch using the same clustering criterion. We conducted a case study, involving 13 software systems, to draw our comparisons. There is a dual benefit to making these comparisons. Specifically, we gain insight into (1) the quality of the spectral methods solutions; and (2) the proximity of the results produced by Bunch to the optimal solution.
Metrics
Details
- Title
- Applying spectral methods to software clustering
- Creators
- A Shokoufandeh - Drexel UniversityS Mancoridis - Drexel UniversityM Maycock - Drexel University
- Publication Details
- Ninth Working Conference on Reverse Engineering, 2002. Proceedings, v 2002-, pp 3-10
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000179731500001
- Scopus ID
- 2-s2.0-19044388343
- Other Identifier
- 991019168322604721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Software Engineering
- Engineering, Electrical & Electronic