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» A Factor Graph Model for Software Bug Finding
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ICSE
2004
IEEE-ACM
14 years 7 months ago
Finding Latent Code Errors via Machine Learning over Program Executions
This paper proposes a technique for identifying program properties that indicate errors. The technique generates machine learning models of program properties known to result from...
Yuriy Brun, Michael D. Ernst
APSEC
2006
IEEE
14 years 1 months ago
Project Replayer with Email Analysis - Revealing Contexts in Software Development
In many software development projects, people tend to repeat same mistakes due to lack of shared knowledge from past experiences. Generally, it is very difficult to manually find ...
Kimiharu Okura, Keita Goto, Noriko Hanakawa, Shinj...
SEMWEB
2005
Springer
14 years 1 months ago
Finding and Ranking Knowledge on the Semantic Web
Abstract. Swoogle helps software agents and knowledge engineers find Semantic Web knowledge encoded in RDF and OWL documents on the Web. Navigating such a Semantic Web on the Web ...
Li Ding, Rong Pan, Timothy W. Finin, Anupam Joshi,...
HICSS
2003
IEEE
202views Biometrics» more  HICSS 2003»
14 years 29 days ago
Adoption Process of Upgrading Software: An Empirical Study of Windows XP
There are many studies in Information Systems on the adoption of new innovations. This paper, on the other hand, presents the findings of an empirical study, which explores factor...
Michael C. L. Lai, Susanna S. Y. Ho, Wendy W. Y. H...
PLDI
2010
ACM
14 years 5 months ago
Pacer: Proportional Detection of Data Races
Data races indicate serious concurrency bugs such as order, atomicity, and sequential consistency violations. Races are difficult to find and fix, often manifesting only in deploy...
Michael D. Bond, Katherine E. Coons, Kathryn S. Mc...