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PROMISE
2010
13 years 1 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
CORR
2010
Springer
134views Education» more  CORR 2010»
13 years 7 months ago
Effective Defect Prevention Approach in Software Process for Achieving Better Quality Levels
Defect prevention is the most vital but habitually neglected facet of software quality assurance in any project. If functional at all stages of software development, it can condens...
V. Suma, T. R. Gopalakrishnan Nair
BMCBI
2008
144views more  BMCBI 2008»
13 years 7 months ago
WGCNA: an R package for weighted correlation network analysis
Background: Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method ...
Peter Langfelder, Steve Horvath
TSMC
1998
99views more  TSMC 1998»
13 years 6 months ago
Learning visually guided grasping: a test case in sensorimotor learning
Abstract—We present a general scheme for learning sensorimotor tasks which allows rapid on-line learning and generalization of the learned knowledge to unfamiliar objects. The sc...
Ishay Kamon, Tamar Flash, Shimon Edelman
DAC
2003
ACM
14 years 8 months ago
A scalable software-based self-test methodology for programmable processors
Software-based self-test (SBST) is an emerging approach to address the challenges of high-quality, at-speed test for complex programmable processors and systems-on chips (SoCs) th...
Li Chen, Srivaths Ravi, Anand Raghunathan, Sujit D...