 |
Conference papers
Mining Architectural Patterns Using Association Rules
Abstract : Software systems usually follow many programming rules prescribed in an architectural model. However, developers frequently violate these rules, introducing architectural drifts in the source code. In this paper, we present a data mining approach for architecture conformance based on a combination of static and historical software analysis. For this purpose, the proposed approach relies on data mining techniques to extract structural and historical architectural patterns. In addition, we propose a methodology that uses the extracted patterns to detect both absences and divergences in source-code based architectures. We applied the proposed approach in an industrial strength system. As a result we detected 137 architectural violations, with an overall precision of 41.02%.
Cited literature [20 references]
https://hal.inria.fr/hal-00854851
Contributor : Lse Lse <>
Submitted on : Wednesday, August 28, 2013 - 11:35:41 AM
Last modification on : Monday, April 20, 2020 - 10:30:15 AM
Long-term archiving on: : Monday, December 2, 2013 - 8:49:37 AM
Contributor : Lse Lse <>
Submitted on : Wednesday, August 28, 2013 - 11:35:41 AM
Last modification on : Monday, April 20, 2020 - 10:30:15 AM
Long-term archiving on: : Monday, December 2, 2013 - 8:49:37 AM
File
2013_seke_archlint.pdf
Files produced by the author(s)