Conference proceeding
Improving the Efficiency of Dependency Analysis in Logical Decision Models
2009 IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING, PROCEEDINGS
01 Jan 2009
Abstract
To address the problem that existing software dependency extraction methods do not work on higher-level software artifacts, do not express decisions explicitly, and do not reveal implicit or indirect dependencies, our recent work explored the possibility of formally de. ning and automatically deriving a pairwise dependence relation from an augmented constraint networks (ACN) that models the assumption relation among design decisions. The current approach is difficult to scale, requiring constraint solving and solution enumeration. We observe that the assumption relation among design decisions for most software systems can be abstractly modeled using a special form of ACN. For these more restrictive, but highly representative models, we present an O(n(3)) algorithm to derive the dependency relation without solving the constraints. We evaluate our approach by computing design structure matrices for existing ACNs that model multiple versions of heterogenous real software designs, often reducing the running time from hours to seconds.
Metrics
Details
- Title
- Improving the Efficiency of Dependency Analysis in Logical Decision Models
- Creators
- Sunny Wong - Drexel UniversityYuanfang Cai - Drexel UniversityIEEE
- Publication Details
- 2009 IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING, PROCEEDINGS
- Series
- IEEE ACM International Conference on Automated Software Engineering
- Publisher
- IEEE
- Number of pages
- 12
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000278137400015
- Scopus ID
- 2-s2.0-77952230314
- Other Identifier
- 991019167560804721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Software Engineering
- Engineering, Electrical & Electronic