Adaptive Weighting of Structural Dependency and Textual Similarity in Software Architecture Recoveryopen access
- Authors
- Um, Jae-Chul; Lee, Ki-Seong; Lee, Chan Gun
- Issue Date
- Mar-2016
- Publisher
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- Keywords
- software architecture recovery; module view; dependency; Newman modularity; information entropy
- Citation
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E99D, no.3, pp 756 - 759
- Pages
- 4
- Journal Title
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- Volume
- E99D
- Number
- 3
- Start Page
- 756
- End Page
- 759
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/7244
- DOI
- 10.1587/transinf.2015EDL8160
- ISSN
- 1745-1361
- Abstract
- Software architecture recovery techniques are often adopted to derive a module view of software from its source code in case software architecture documents are unavailable or outdated. The module view is one of the most important perspectives of software architecture. In this paper, we propose a novel approach to derive a module view by adaptively integrating structural dependency and textual similarity. Our approach utilizes Newman modularity and Shannon information entropy to determine the appropriate weights of the dependencies during the integration. We apply our approach to various open-source projects and show the experimental results validating the effectiveness of the approach.
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- Appears in
Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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