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Reducing Features to Improve Bug Prediction
Found in: Automated Software Engineering, International Conference on
By Shivkumar Shivaji, E. James Whitehead Jr., Ram Akella, Sunghun Kim
Issue Date:November 2009
pp. 600-604
Recently, machine learning classifiers have emerged as a way to predict the existence of a bug in a change made to a source code file. The classifier is first trained on software history data, and then used to predict bugs. Two drawbacks of existing classi...
 
Predicting method crashes with bytecode operations
Found in: Proceedings of the 6th India Software Engineering Conference (ISEC '13)
By Nicolas Bettenburg, Rahul Premraj, Shivkumar Shivaji, Sunghun Kim, Thomas Zimmermann
Issue Date:February 2013
pp. 3-12
Software monitoring systems have high performance overhead because they typically monitor all processes of the running program. For example, to capture and replay crashes, most current systems monitor all methods; thus yielding a significant performance ov...
     
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