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ICSE
2007
IEEE-ACM
14 years 9 months ago
Feedback-Directed Random Test Generation
We present a technique that improves random test generation by incorporating feedback obtained from executing test inputs as they are created. Our technique builds inputs incremen...
Carlos Pacheco, Shuvendu K. Lahiri, Michael D. Ern...
ICSE
2008
IEEE-ACM
14 years 9 months ago
ARTOO: adaptive random testing for object-oriented software
Intuition is often not a good guide to know which testing strategies will work best. There is no substitute for experimental analysis based on objective criteria: how many bugs a ...
Ilinca Ciupa, Andreas Leitner, Manuel Oriol, Bertr...
VMCAI
2005
Springer
14 years 2 months ago
Minimizing Counterexample with Unit Core Extraction and Incremental SAT
Abstract. It is a hotly researching topic to eliminate irrelevant variables from counterexample, to make it easier to be understood. K Ravi proposes a two-stages counterexample min...
ShengYu Shen, Ying Qin, Sikun Li
CVPR
2009
IEEE
14 years 7 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
PAMI
2010
215views more  PAMI 2010»
13 years 7 months ago
Fusion Moves for Markov Random Field Optimization
—The efficient application of graph cuts to Markov Random Fields (MRFs) with multiple discrete or continuous labels remains an open question. In this paper, we demonstrate one p...
Victor S. Lempitsky, Carsten Rother, Stefan Roth, ...