Title :
Data Mining for Software Engineering
Author :
Xie, Tao ; Thummalapenta, Suresh ; Lo, David ; Liu, Chao
Author_Institution :
North Carolina State Univ., Raleigh, NC, USA
Abstract :
To improve software productivity and quality, software engineers are increasingly applying data mining algorithms to various software engineering tasks. However, mining SE data poses several challenges. The authors present various algorithms to effectively mine sequences, graphs, and text from such data.
Keywords :
data mining; software quality; data graphs; data mining; data sequences; software engineering; software productivity; software quality; text mining; Cleaning; Clustering algorithms; Data engineering; Data mining; Databases; Debugging; Dynamic programming; Pattern matching; Software algorithms; Software engineering; Computational intelligence; Data mining; Design and test; Software engineering;
DOI :
10.1109/MC.2009.256
