DocumentCode :
3194875
Title :
Machine learning and software engineering
Author :
Zhang, El ; Tsai, Jeffrey J P
Author_Institution :
Dept. of Comput. Sci., California State Univ., Sacramento, CA, USA
fYear :
2002
fDate :
2002
Firstpage :
22
Lastpage :
29
Abstract :
Machine learning deals with the issue of how to build programs that improve their performance at some task through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This paper deals with the subject of applying machine learning methods to so are engineering. In the paper, we first provide the characteristics and applicability of some frequently utilized machine learning algorithms. We then summarize and analyze the existing work and discuss some general issues in this niche area. Finally we offer some guidelines on applying machine learning methods to software engineering tasks.
Keywords :
learning (artificial intelligence); software engineering; software quality; software reliability; application domains; machine learning; software engineering; software maintenance; Application software; Artificial intelligence; Electrical capacitance tomography; Guidelines; Learning systems; Machine learning; Maintenance engineering; Programming; Software engineering; Software maintenance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings. 14th IEEE International Conference on
ISSN :
1082-3409
Print_ISBN :
0-7695-1849-4
Type :
conf
DOI :
10.1109/TAI.2002.1180784
Filename :
1180784
Link To Document :
بازگشت