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High-frequency dynamics of type B glass formers investigated by broadband dielectric spectroscopy
High-frequency dynamics of type B glass formers investigated by broadband dielectric spectroscopy
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High-frequency dynamics of type B glass formers investigated by broadband dielectric spectroscopy

Kastner, S. ; Köhler, M. ; Goncharov, Y. ; Lunkenheimer, P. ; Loidl, A.

Journal of non-crystalline solids, 2011-01, Vol.357 (2), p.510-514 [Periódico revisado por pares]

Elsevier B.V

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DeepGauge: multi-granularity testing criteria for deep learning systems
DeepGauge: multi-granularity testing criteria for deep learning systems
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Ata de Congresso 		Adicionar ao Meu Espaço

DeepGauge: multi-granularity testing criteria for deep learning systems

Ma, Lei ; Juefei-Xu, Felix ; Zhang, Fuyuan ; Sun, Jiyuan ; Xue, Minhui ; Li, Bo ; Chen, Chunyang ; Su, Ting ; Li, Li ; Liu, Yang ; Zhao, Jianjun ; Wang, Yadong

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.120-131

New York, NY, USA: ACM

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ContractFuzzer: fuzzing smart contracts for vulnerability detection
ContractFuzzer: fuzzing smart contracts for vulnerability detection
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ContractFuzzer: fuzzing smart contracts for vulnerability detection

Jiang, Bo ; Liu, Ye ; Chan, W. K.

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.259-269

New York, NY, USA: ACM

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4
Improving automatic source code summarization via deep reinforcement learning
Improving automatic source code summarization via deep reinforcement learning
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Improving automatic source code summarization via deep reinforcement learning

Wan, Yao ; Zhao, Zhou ; Yang, Min ; Xu, Guandong ; Ying, Haochao ; Wu, Jian ; Yu, Philip S.

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.397-407

New York, NY, USA: ACM

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5
FairFuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage
FairFuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage
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FairFuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage

Lemieux, Caroline ; Sen, Koushik

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.475-485

New York, NY, USA: ACM

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6
Concolic testing for deep neural networks
Concolic testing for deep neural networks
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Concolic testing for deep neural networks

Sun, Youcheng ; Wu, Min ; Ruan, Wenjie ; Huang, Xiaowei ; Kwiatkowska, Marta ; Kroening, Daniel

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.109-119

New York, NY, USA: ACM

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7
αDiff: cross-version binary code similarity detection with DNN
αDiff: cross-version binary code similarity detection with DNN
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αDiff: cross-version binary code similarity detection with DNN

Liu, Bingchang ; Huo, Wei ; Zhang, Chao ; Li, Wenchao ; Li, Feng ; Piao, Aihua ; Zou, Wei

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.667-678

New York, NY, USA: ACM

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8
Testing autonomous cars for feature interaction failures using many-objective search
Testing autonomous cars for feature interaction failures using many-objective search
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Testing autonomous cars for feature interaction failures using many-objective search

Abdessalem, Raja Ben ; Panichella, Annibale ; Nejati, Shiva ; Briand, Lionel C. ; Stifter, Thomas

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.143-154

New York, NY, USA: ACM

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9
Automated directed fairness testing
Automated directed fairness testing
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Automated directed fairness testing

Udeshi, Sakshi ; Arora, Pryanshu ; Chattopadhyay, Sudipta

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.98-108

New York, NY, USA: ACM

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API method recommendation without worrying about the task-API knowledge gap
API method recommendation without worrying about the task-API knowledge gap
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API method recommendation without worrying about the task-API knowledge gap

Huang, Qiao ; Xia, Xin ; Xing, Zhenchang ; Lo, David ; Wang, Xinyu

2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE), 2018, p.293-304

New York, NY, USA: ACM

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