Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

Locating Matching Rules by Mining Software Change Log

Authors
Ming-Shi Wang 0, Jung-te Weng
Corresponding Author
Ming-Shi Wang
0IEICE
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.303How to use a DOI?
Keywords
Software maintenance, Data mining, Neural Network
Abstract
A software system maintenance activity is typically performed under an environment of lacking knowledge about how to process it. This scarcity of knowledge may be caused by various factors, such as the large size and complexity of the systems, high staff turnover, poor documentation and long-term system maintenance. The study applies Apriori algorithm to extract information from software change logs. Unfortunately, the software change logs generate many rules. Because searches the suitable rule from many rules is difficult and important matter, especially. This study focuses on the software co-change dependency and proposes a classification model based on association mining, to deal with such kind of dependency. The model combines data mining technologies, the traditional decision-tree and neural learning capabilities, to handle the complicated and real cases, and then improve the rule searching efficiency and the matching accuracy.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.303How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ming-Shi Wang
AU  - Jung-te Weng
PY  - 2006/10
DA  - 2006/10
TI  - Locating Matching Rules by Mining Software Change Log
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.303
DO  - https://doi.org/10.2991/jcis.2006.303
ID  - Wang2006/10
ER  -