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» A Machine Learning Approach for Statistical Software Testing
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TSE
2008
129views more  TSE 2008»
14 years 9 months ago
Classifying Software Changes: Clean or Buggy?
This paper introduces a new technique for predicting latent software bugs, called change classification. Change classification uses a machine learning classifier to determine wheth...
Sunghun Kim, E. James Whitehead Jr., Yi Zhang 0001
ICSE
2010
IEEE-ACM
15 years 2 months ago
Summarizing software artifacts: a case study of bug reports
Many software artifacts are created, maintained and evolved as part of a software development project. As software developers work on a project, they interact with existing projec...
Sarah Rastkar, Gail C. Murphy, Gabriel Murray
NIPS
1998
14 years 11 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
15 years 1 months ago
Memory analysis and significance test for agent behaviours
Many agent problems in a grid world have a restricted sensory information and motor actions. The environmental conditions need dynamic processing of internal memory. In this paper...
DaeEun Kim
ECTEL
2010
Springer
14 years 11 months ago
Deep Learning Design for Sustainable Innovation within Shifting Learning Landscapes
Changes in the underpinning technologies for TEL is occurring at a pace that we have never before experienced, and this is unlikely to slow down. This necessitates a broader and mo...
Andrew Ravenscroft, Tom Boyle, John Cook, Andreas ...