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» A Machine Learning Approach for Statistical Software Testing
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131
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TSE
2008
129views more  TSE 2008»
15 years 2 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
119
Voted
ICSE
2010
IEEE-ACM
15 years 7 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
127
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NIPS
1998
15 years 3 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
118
Voted
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
15 years 6 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
15 years 3 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 ...