DocumentCode
1999433
Title
Data mining in functional test content optimization
Author
Li-C Wang
Author_Institution
Univ. of California at Santa Barbara, Santa Barbara, CA, USA
fYear
2015
fDate
19-22 Jan. 2015
Firstpage
308
Lastpage
315
Abstract
This paper reviews the data mining methodologies proposed for functional test content optimization where tests are sequences of instructions or transactions. Basic machine learning concepts and the key ideas of these methodologies are explained. Challenges for implementing these methodologies in practice are illustrated. Promises are demonstrated through experimental results based on industrial verification settings.
Keywords
data mining; learning (artificial intelligence); optimisation; data mining; functional test content optimization; industrial verification settings; machine learning; Assembly; Context; Data mining; Generators; Kernel; Machine learning algorithms; Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Design Automation Conference (ASP-DAC), 2015 20th Asia and South Pacific
Conference_Location
Chiba
Print_ISBN
978-1-4799-7790-1
Type
conf
DOI
10.1109/ASPDAC.2015.7059023
Filename
7059023
Link To Document