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» Evaluating machine creativity
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SIGSOFT
2008
ACM
16 years 4 months ago
Finding programming errors earlier by evaluating runtime monitors ahead-of-time
Runtime monitoring allows programmers to validate, for instance, the proper use of application interfaces. Given a property specification, a runtime monitor tracks appropriate run...
Eric Bodden, Patrick Lam, Laurie J. Hendren
123
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CF
2007
ACM
15 years 7 months ago
Fast compiler optimisation evaluation using code-feature based performance prediction
Performance tuning is an important and time consuming task which may have to be repeated for each new application and platform. Although iterative optimisation can automate this p...
Christophe Dubach, John Cavazos, Björn Franke...
CGO
2009
IEEE
15 years 10 months ago
Automatic Feature Generation for Machine Learning Based Optimizing Compilation
Recent work has shown that machine learning can automate and in some cases outperform hand crafted compiler optimizations. Central to such an approach is that machine learning tec...
Hugh Leather, Edwin V. Bonilla, Michael O'Boyle
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
15 years 3 months ago
Superstate identification for state machines using search-based clustering
State machines are a popular method of representing a syshigh level of abstraction that enables developers to gain an overview of the system they represent and quickly understand ...
Mathew Hall, Phil McMinn, Neil Walkinshaw
ICAC
2006
IEEE
15 years 9 months ago
Fast and Effective Worm Fingerprinting via Machine Learning
— As Internet worms become ever faster and more sophisticated, it is important to be able to extract worm signatures in an accurate and timely manner. In this paper, we apply mac...
Stewart M. Yang, Jianping Song, Harish Rajamani, T...