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